KR101212321B1 - System and method for alternative simulation of logistics infrastructure - Google Patents

Abstract

Logistics Infrastructure Countermeasure Simulation System and simulation method are used to refine the data operated in the logistics infrastructure to generate future quantities through demand forecast. In addition, it is possible to analyze the infrastructure load due to future year volume, so you can choose the countermeasure through load analysis, and it is possible to establish and change various mid-to-long-term infrastructure construction plans in a short time.

Logistics Infrastructure, Countermeasures, Simulation, Postal Logistics, Load Analysis, Verification

Description

System and method for alternative simulation of logistics infrastructure

The present invention relates to a logistics infrastructure countermeasure simulation system and method thereof.

The present invention is derived from a study conducted as part of the postal technology research and development project of the Ministry of Knowledge Economy [Task Management Number: 2006-X-001-03, Task name: Real-time postal logistics element technology development].

In general, the direction of building the logistics infrastructure is to collect operational performance data according to the purpose, define the analysis methodology and the method for infrastructure construction, and then establish alternatives by using tools that can generate the optimal plan for support by hand. Is carried out in a manner. In order to perform such a method and process improvement in a short-term base, the modeled model is applied after the simulation.

In this case, it takes a lot of time to collect data for improving the process and collecting data for the purpose of establishing the infrastructure, coordinating the jurisdiction for load balancing between the delivery country and the distribution center. In addition, these methods should perform the same task repeatedly whenever necessary because the response plan is established by referring to various methodologies according to the requirements for establishing each countermeasure.

In addition, it is necessary to generate and utilize data for establishing countermeasures by demand forecasting method, and it is not easy to grasp what problems exist in and between bases of actual infrastructure, and it is not possible to verify the short-term countermeasures in advance. It is not possible to verify the feasibility of problems that may occur when applied to the environment.

Accordingly, there is a need for a simulator that allows the use of infrastructure load analysis simulation functions that are described almost identically to the environment of the actual infrastructure, along with supporting the medium and long term logistics infrastructure construction planning. In addition, it is necessary to obtain simulation input data from the existing logistics operation system and use detailed analysis on future volume generation, operation standard data generation and infrastructure load analysis required for establishing the medium and long term logistics infrastructure construction plan.

In addition, it is possible to simulate the postal classification process within the logistics base, the transportation method between the logistics bases, and the delivery station work process, and to identify the loads, transportation loads, communication quality, and operating costs, etc. Is needed.

Accordingly, the present invention provides a simulation system and method that can generate the countermeasures necessary for establishing the infrastructure construction plan, and can verify the generated countermeasures in advance.

Logistics infrastructure countermeasure simulation system which is one feature of the present invention for achieving the technical problem of the present invention,

A user interface unit which receives data from the outside or provides information generated by the system; A data statistics analyzer for converting the information into a preset format for analyzing data output from the postal logistics information system linked with the system; A simulation unit configured to perform operations and transportation simulations based on data output from the user interface or data output from the data statistical analysis unit; A countermeasure establishment unit for establishing and outputting a countermeasure according to the data output from the user interface unit; And an information storage unit for storing reference information for simulation, simulation result information, and corresponding method information.

Method for simulating the logistics infrastructure correspondence that is another feature of the present invention for achieving the technical problem of the present invention,

When the demand forecast data for any one of the base year or any year is received, analyzing the annual load based on the demand forecast data to generate load analysis information for each year; Establishing a corresponding plan for each year based on the generated load analysis information for each year; And establishing a countermeasure by analyzing detailed loads of the countermeasures based on the established countermeasures for each year.

According to an embodiment of the present invention, since the data operated in the logistics infrastructure may be purified to generate future quantities through demand forecasting, and the infrastructure load may be analyzed by future year quantities, a countermeasure through load analysis may be selected. .

In addition, it is possible to establish and change various mid- to long-term infrastructures in a short time, and verify the established countermeasures.

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.

Throughout the specification, when a part is said to "include" a certain component, it means that it can further include other components, without excluding other components unless specifically stated otherwise.

Hereinafter, a system and method for simulating logistics infrastructure response according to an exemplary embodiment of the present invention will be described with reference to the accompanying drawings.

1 is a system structural diagram according to an embodiment of the present invention.

As shown in FIG. 1, the system according to an exemplary embodiment of the present invention includes a user interface unit 100, a data statistical analyzer 200, a simulation unit 300, a corresponding plan establishment unit 400, and an information storage unit ( 500).

First, the user interface unit 100 receives various data from a user or provides a user with information generated in the system, and establishes a data input unit 110, a simulation and a result inquiry unit 120, and a corresponding method. The result inquiry unit 130 is included.

The data input unit 110 is connected to information input means used by a user, such as logistics planning and operation personnel, to collect data input from the user. In addition, the data received from the user is transmitted to the data statistical analysis unit 200.

The simulation execution and result search unit 120 receives data input through the data input unit 110 in conjunction with the simulation unit 300 and delivers the data to the simulation unit 300 or by using the data in the simulation unit 300. It receives the simulation result and provides the result to the user.

The response plan establishment and result retrieval unit 130 interlocks with the response plan establishment unit 400 to transfer data collected by the data input unit 110 or data performed by the simulation unit 300 to output based on the data. Make a plan. In addition, the response method establishment unit receives the results of the data-related response method generated by the provided to the user.

Next, the data statistics analyzing unit 200 converts the information to a preset format for analyzing information transmitted from the postal logistics information system (PostNet). To this end, the data statistical analyzer 200 includes a data migration unit 210, an input data converter 220, and an output data converter 230.

The data migration unit 210 converts the data received from the postal logistics information system or the data received from the user interface unit 100 into a data form required for establishing a long-term response plan and simulating infrastructure load analysis. This conversion of data types allows the generation of reference year input data required for the simulation in advance.

The input data conversion unit 220 generates a simulation input quantity information by generating a future year input quantity based on a reference year quantity into which the demand forecast information is input by the user with reference to a predetermined demand forecast generation result required for starting the simulation. It occurs as the result data of the simulation. To this end, the input data conversion unit 220 is largely divided into a recorded mail input data converter 221, a non-recorded mail input data converter 222, an operation and transport standard data converter 223, and a future mail volume data generator 224. It is composed. The detailed structure of the input data converter 220 will be described later.

The output data converter 230 converts simulation result data into output data such as load and communication quality in order to provide a user with a simulation result generated from the input data converter 220. In other words, about the logistics infrastructure, by year, by logistics base, by day, by time, by postal type, by work condition, and by information from the receiving country to the delivery country, the simulation input data volume is based on the actual year of operation performance and the demand forecasting method. Generated as simulation input quantities for preliminary evaluation of future years.

Next, the simulation unit 300 performs the simulation of the user interface unit 100 and based on the data transmitted from the result inquiry unit 120 or the data input from the data statistical analyzer 200, operation and transportation according to the corresponding data. Perform a simulation on. The simulation unit 300 includes an operation process simulation unit 310 and a transportation process simulation unit 320.

When statistical simulation data output from the data statistical analysis unit 200 or data is input from the user interface unit 100, the operation process simulation unit 310 may be a base (for example, a transportation exchange center, a concentration station, a distribution center, or a delivery station). Etc.) Perform simulations of internal operational process logic. Through simulation, modeling the operating process for the current operating base for each base, calculate the base load for the input quantity.

The transport process simulation unit 320 is a transport network (for example, an exchange network between an exchange center and a central station, a concentration station between a central office and a distribution center, etc.) for transportation between the logistics bases as a result of the operation process simulation unit 310 performed within the logistics base. Simulation of the transport process in the network, central office and post office network). The current transport process is modeled by transport network to calculate the number of vehicles required and the cost of transport.

Next, when the corresponding method establishing unit 400 receives data from the user interface unit 100, it establishes a corresponding method according to the received data and provides the same to the user. The countermeasure establishment unit 400 according to the embodiment of the present invention includes an infrastructure establishment unit 410, a jurisdiction zone design unit 420, a network structure design unit 430, and a processing capability adjustment unit 440.

The infrastructure establishment unit 410 establishes an infrastructure based on a simulation result for future quantities. With the new infrastructure, the capacity and jurisdiction of the new infrastructure can be established to rebalance the infrastructure load.

The jurisdiction design unit 420 recalculates the conventional and parcel jurisdiction of the existing infrastructure and recalculates the load for each infrastructure. The network structure design unit 430 designs the network structure through the establishment of the exchange center, the exchange time, the exchange zone setting, and the like, and generates reference information of the simulation.

The processing capacity adjusting unit 440 usually redesigns the jurisdiction by adjusting the functions of the existing infrastructure such as parcels dedicated, and adjusts the processing capacity within the logistics base by recalculating the load of the infrastructure by adjusting the processing capacity of the overload infrastructure. do.

Next, the information storage unit 500 is an operation / transportation reference data storage unit 510 for storing the reference information for the simulation, the simulation result data storage unit 520 to receive and store the simulation results received from the simulation unit 300 And a countermeasure data storage unit 530 that stores the countermeasure established by the countermeasure establishment unit 400.

The components of the system described above will be described in more detail with reference to the accompanying drawings.

First, referring to the components of the data statistical analysis unit 200, the data statistical analysis unit 200 is required to start the simulation and the data migration unit 210 for generating the reference year input data required for the simulation in advance. When the demand forecast information is input, the future year input volume is generated based on the base year volume. At this time, in performing an operation in the input data converter 220 to generate the corresponding data as simulation input quantity data, the input quantity data is classified as shown in FIG. 2 and generated based on the postal type 4.

2 is an exemplary view showing input data generation criteria for each mail type according to an embodiment of the present invention.

As illustrated in FIG. 2, the postal type according to the embodiment of the present invention is divided into four types, but is not necessarily limited thereto.

Reception desks in the postal logistics information system are classified as either recorded or unrecorded mail. Therefore, parcels, which are recorded mails, and specialty mails and non-recorded mails, which are classified into small and large, are generated by inputting data for each base for simulation. The criteria for the postal work conditions are divided into manual, mechanical, and line classification, as in postal type 4, and the line classification mail volume is classified into line classification mail 1 and line classification mail 2 so as to match the conditions of dispatch and arrival. To create.

In the case of large normal mail, the line item mail reflects the same conditions as the small mail volume calculation standard, and the remaining mails are calculated in the general volume. The volume data for the demand forecast is generated based on the postal type 2, and the volume is generated for each point by year, and used when generating the demand forecast value. And if the machine quantity exists, it can be defined as small.

In order to perform the volume calculation process for extracting the postal quantity information, which is indicated by the recorded post in the reception desk on the postal logistics information system, from the postal logistics information system and providing it as input data for the simulation, A recording postal input data converter 221 that is a configuration of the input data conversion unit 220 according to an embodiment of the present invention will be described with reference to FIG. 3.

3 is an exemplary diagram of a recorded mail input data converter structure of an input data converter according to an embodiment of the present invention.

As shown in FIG. 3, the recorded mail input data converter 221 according to the embodiment of the present invention includes a first quantity generating module 221-1, a second quantity generating module 221-2, and a ratio value generating module. 221-3, an input reference quantity data generation module 221-4, and an input quantity generation module 221-5.

The first quantity generation module 221-1 extracts quantity data for each reception point / type / day from among the data received from the recorded mail item reception desk of the postal logistics information system and converted by the data migration unit 210, respectively. Save it. Then, in the postal log information receiving unit of the postal logistics information system, using the delivery flag registration code code value corresponding to the recipient postal code number corresponding to the recipient address serial number, the reception volume is generated and stored for each country / day. In addition, the daily volume value and the time-based volume meter value is generated, and the time-phased volume ratio value is generated and stored.

The second quantity generating module 221-2 generates and stores the first generalizing station (or dispatching generalizing station) and the second generalizing station (or arriving generalizing station) quantity values according to the execution result of the first quantity generating module 221-1. .

When the input reference quantity data generation module 221-4 receives a message including the future year simulation period information, the future year growth rate value information, and the simulation execution request information from the user interface 100, performing the corresponding year, month and month simulations. Generate input reference quantity data for each base point for the period.

The input quantity generation module 221-5 performs an operation of generating the reference year input quantity as the simulation input quantity in the case of the reference year simulation, and if the future year quantity increase rate value exists, the second quantity generation module 221-2 or After the execution of the input reference quantity data generation module 221-4 is completed, the simulation input quantity is generated.

Next, during the above-mentioned execution process, a volume calculation process is performed to extract postal volume information marked as unrecorded posts in the reception center on the postal logistics information system from the postal logistics information system and provide it as input data for simulation. To be described, a non-recorded postal item input data converter 222, which is a second configuration of the input data converter 220 according to an embodiment of the present invention, will be described with reference to FIG.

4 is an exemplary diagram of an unrecorded postal input data converter structure of an input data converter according to an embodiment of the present invention.

As shown in FIG. 4, the non-recorded mail input data converter 222 according to the second embodiment includes a quantity data extraction module 222-1, an input reference quantity data generation module 222-2, and manually generated quantity data. The generation module 222-3, the simulation input data generation module 222-4, and the delivery quantity ratio generation module 222-5 are included.

The quantity data extraction module 222-1 extracts and stores quantity data for each work condition for each post and daily mail type. Here, the quantity data by work condition by base and daily mail type refers to the data generated by daily, day of week, special communication period, or work condition by the type of mail by reception base in the unrecorded mail reception desk of the postal logistics information system. do.

The input reference quantity data generation module 222-2 generates and stores a ratio value based on the shipment, arrival / distribution quantity values of each base from the operational quantity data in the recorded mail item receiving unit of the postal logistics information system. In addition, the first and second overall station volume values are generated and stored. In this case, when the future year quantity input data is not transmitted from the user interface unit 100, the manual generation quantity generation data generation module 222-3 may be called.

When the dividend amount ratio generation module 222-5 obtains a request message including future year simulation period information, future year growth rate value information, and simulation execution request information from the user interface 100, the simulation is performed on the corresponding day. Generate baseline volume data for each base point for the risk period.

The manual generation volume data generation module 222-3 generates a manual operation volume ratio value after the machine operation generated and stored from the classification facility operation performance data acquisition function among the data of the postal logistics information system, Multiply the quantities to generate additional manually generated quantities and store them.

To this end, it is determined whether there is a manually generated volume ratio value after the divided machine operation generated from the operational data, and if there is no manual generated volume ratio value, it is requested to calculate an additional manually generated quantity in the separated facility operation performance data. After that, if the value of the amount of manual work generated after the machine operation is generated from the classification facility operating performance data, this value is multiplied by the amount of machine generated work for each base to generate additional manual work generated.

The simulation input data generation module 222-4 receives the simulation start information from the input reference quantity data generation module 222-2, and in the case of the reference year simulation, the simulation input quantity based on the equal distribution value of the reference year input quantity. To occur. At this time, if a future year quantity increase rate value exists, after the execution of the delivery rate ratio generation module 222-5 is completed, the simulation input quantity is generated based on the uniform distribution value.

Next, among the system structure mentioned in FIG. 1, the operation and transportation standard data converter of the input data conversion unit 220 which can extract and provide the operation standard data required to perform the simulation function from the postal logistics information system ( The structure will be described with reference to FIG. 5.

5 is an exemplary view illustrating a structure of an operation and transport reference data converter of an input data converter according to an exemplary embodiment of the present invention.

As shown in FIG. 5, the operation and transportation reference data converter 223 may include the operation reference information generation module 223-1, operation time quantity calculation module 233-2, and ratio value generation module for obtaining operation data. And (233-3), a manual generation quantity calculation module 233-4, a fastening quantity data generation module 233-5 for obtaining transportation data, and a transportation distance fee data generation module 233-6.

The work criterion information generation module 233-1 is configured to generate the type and processing capability of the facility and the work condition reference information for each facility from the information inputted from the operation management data of the postal logistics information system and converted by the data migration unit 210. After extraction, the data is transferred to and stored in the operation / transportation reference data storage 510. As shown in FIG. 5, the operation / transport reference data storage unit 510 includes an operation reference data storage unit 510-1, an operation standard quantity data storage unit 510-2, and a transport reference data storage unit 510-3. The information extracted by the job reference information generation module 233-1 may be stored in the operation reference data storage 510-1.

The processing time amount calculation module 233-2 for each time slot refers to a case in which the user inputs processing capacity of the facility for each location based on information inputted from operation management data of the postal logistics information system and converted by the data migration unit 210. In order to obtain the processing capability data for each time slot. Then, based on the acquired data, the amount of time-processed volume of the facility for each location is generated and delivered to the operation reference data storage 510-1.

The ratio value generation module 233-3 generates the dispatch / arrival / distribution quantity and ratio value for each base from the information inputted from the operation management data of the postal logistics information system and converted by the data migration unit 210. The generated shipment / arrival / distribution volume and ratio values for each base point are transmitted to and stored in the operation standard quantity data storage 510-2.

The manual generation quantity calculation module 233-4 is a machine processing of the quantity of water supplied for processing the machine through the classification facilities for each base from the information inputted from the operation management data of the postal logistics information system and converted in the data migration unit 210. It is not possible to generate a ratio value of the quantity generated by hand quantity. The ratio value of the generated quantity is transferred to the operation standard quantity data storage 510-2 and stored. And after calculating the amount of manual work generated by machine processing for each base, the calculated information is also delivered to the operation standard data storage unit 510-2 and stored.

The fastening quantity data generation module 233-5 performs a simulation process of acquiring transport data in order to extract and provide transport reference data required for performing a simulation function from the postal logistics information system. From the information input from the operation management data and converted in the data migration unit 210, to obtain the fastening quantity data per parcel pallet. The acquired fastening quantity data per parcel pallet is transferred to and stored in the transportation reference data storage 510-3.

The transportation distance fee data generation module 233-6 obtains the transportation fee data from information inputted from the operation management data of the postal logistics information system and converted by the data migration unit 210. The obtained data is transferred to and stored in the transportation reference data storage 510-3.

Next, the structure of the demand forecast and future mail volume generator 224 that generates and provides a demand forecast volume for establishing a response plan through the infrastructure load analysis based on the future year, among the system structure mentioned in FIG. This will be described with reference to 6.

6 is an exemplary view illustrating a demand prediction and future mail quantity generation module structure of an input data converter according to an exemplary embodiment of the present invention.

As shown in FIG. 6, the demand forecasting and future mail quantity generator 224 includes a quantity data generation module 224-1, a reference data generation module 224-2, and a quantity variation generation module 224-3. .

The quantity data generation module 224-1 calculates the daily or monthly quantity for each base based on the daily quantity data of the reception desk part of the postal logistics information system. The reference data generation module 224-2 calculates the quantity of each base by year based on the result of calculating the daily quantity by each base calculated by the quantity data generation module 224-1. Here, by base means a general office or a postal application, but is not necessarily limited to this.

The quantity change generation module 224-3 may generate a CAGR (national or blue) by using the previous year's quantity data and the newly generated reference variable quantity value to calculate the demand forecast and the future mail quantity in the input data converter 220. Create and store Compound Annual Growth Rate. In addition, when the demand prediction information is input from the user interface unit 100, it generates a quantity change rate.

At this time, in order to generate the rate of change of the volume, after supplying the increase and decrease rate data for each mail type and logistics base stored in the information storage unit 500 when the simulation unit 300 is driven, the mail type, national demand forecast If the increase / decrease value is obtained by increasing / decreasing the amount, the change of future year volume by base is generated. Thereafter, when the CAGR value for each application is obtained from the user interface unit 100, after the correction is made so that the predicted total volume value for each body application and the total national volume value are matched by the increase / decrease rate value for each body application to match the national demand forecasted volume value. Generates fluctuations in future year volume by base.

Once the volume change rate value for the future year is generated, it is generated above by input quantity generation modules 221-4 and 222-2, respectively located in the recorded mail input data converter 221 and the non-recorded mail input data converter 222, respectively. Information on future year volume changes.

Next, among the system structure mentioned in FIG. 1, the detailed load analysis, vehicle requirement analysis, and communication quality analysis results are converted into output data to provide the user with the results of the infrastructure load analysis simulation. The structure of the output data conversion unit 230 which stores the load calculation result for each central station in the information storage unit 500 and provides the result to the user through the user interface unit 100 will be described with reference to FIG. 7. Let's do it.

7 is a structural diagram of an output data converter according to an exemplary embodiment of the present invention.

As shown in FIG. 7, the output data conversion unit 230 according to an embodiment of the present invention includes a result occurrence checking module 231, a data retrieval module 232, a detailed load analysis module 233, and a vehicle required calculation module. 234 and the postal grade satisfaction rate calculation module 235.

The result occurrence checking module 231 may compare the simulation result and the countermeasure result output from the simulation unit 300 and the counterplan establishment unit 400 with the simulation result data storage unit 520 of the information storage unit 500 and the counterplan. The data is transmitted to and stored in the storage unit 530.

The data retrieval module 232 retrieves data for each operation standard / transportation standard / volume / area stored in the result data storage unit 520 or the corresponding method data storage unit 530, and through the user interface unit 100. To the user.

The detailed load analysis module 233 largely calculates the overload ratio for the logistics bases and calculates the maximum daily load. That is, the detailed load analysis module 233 calculates the overload days and the ratio values from the load values by the dispatching station and the arrival classification by the central station among the simulation results. In addition, from the simulation results, the daily average load value and the daily maximum load value are calculated from the load values for each dispatching station and arrival division for each central station.

The vehicle requirement calculation module 234 calculates a vehicle requirement for each transportation section from the simulation result data in connection with the vehicle requirement analysis, and transmits the result to the information storage unit 500. In addition, the result calculated by the user interface unit 100 is output on the user screen and provided.

In addition, the simulation results may be used to calculate the daily average and the maximum required number of vehicles for each size of the vehicle between the bases. The daily average and daily maximum transportation costs incurred during the simulation period are also calculated to calculate the daily average and maximum daily transportation costs.

The postal type satisfaction rate calculation module 235 calculates a postal type delivery standard satisfaction rate from simulation performance result data in connection with the communication quality analysis, and transmits the calculated result to the information storage unit 500. In addition, the result calculated by the user interface unit 100 is output on the user screen and provided.

Next, the components of the corresponding method establishment unit 400 of FIG. 1 will be described in detail with reference to FIGS. 8 to 10.

8 is a structural diagram of an infrastructure establishment unit of a countermeasure establishment unit according to an embodiment of the present invention. 9 is a structural diagram of the jurisdiction zone design unit of the countermeasure planning unit according to the embodiment of the present invention, and FIG. 10 is a structure diagram of the processing capability adjusting function unit of the countermeasure planning unit according to the embodiment of the present invention.

First, as shown in FIG. 8, the infrastructure establishment unit 410 according to the embodiment of the present invention receives the communication time information and the distance / time setting data from the user interface and stores it as reference data for simulation of the corresponding scheme. In addition, by receiving the processing capacity setting and jurisdiction setting data input, calculate the load for each infrastructure in real time to provide to the user to create and provide an appropriate infrastructure new proposal.

To this end, the infrastructure establishment unit 410 includes an information collection module 411, a classification quantity calculation module 412 for each infrastructure, a new infrastructure processing capacity calculation module 413 and a load calculation module 414 for each infrastructure.

The information collection module 411 receives a communication time and distance / time setting data from the user interface unit 100 and transfers the data to the corresponding method data storage unit 530 of the information storage unit 500 to reference the simulation for the corresponding method. To be stored as data. The information collected by the information collection module 411 is received by the division quantity calculation module 412 and the new infrastructure processing capability calculation module 413 for each infrastructure to calculate the degree of classification and the processing capacity of the new infrastructure.

The infrastructure load calculation module 414 receives the information calculated by the infrastructure quantity calculation module 412 and the new infrastructure processing capability calculation module 413 for each infrastructure, and calculates the load for each infrastructure in real time to the user interface unit 100. Deliver it to the user.

Next, as shown in FIG. 9, the jurisdiction area design unit 420 is for analyzing the effect of coordinating the dispatch and arrival jurisdiction of the commerce and parcels of the centralized and distribution centers. It includes a separate quantity calculation module 422 and load calculation module 423 for each infrastructure.

The setting module 421 receives setting information of a normal shipping jurisdiction, a normal arrival jurisdiction, a parcel sending jurisdiction, and a parcel arrival jurisdiction through the user interface unit 100. Then, based on the standard quantity information stored in the operation standard quantity data storage unit 510-2 and the received information, the infrastructure quantity classification module 422 for each infrastructure and the load calculation module 423 for each infrastructure according to the changed jurisdiction data Estimate infrastructure load in real time. In addition, the newly calculated load-related information for each infrastructure is provided to the user through the user interface unit 100.

In other words, the conventional jurisdiction of the central office uses parcels and parcels in most cases, except for some general bureaus. For example, separate parcels should be set up at the parcel arrival jurisdiction.

Next, as shown in FIG. 10, the processing capacity adjustment function 440 analyzes the function of the existing central office and the distribution center, the adjustment of the division facilities and the manual processing capacity, and the effect of resetting the jurisdiction accordingly. Module 441, exchange time setting module 442, processing capability setting module 443, and exchange area setting module 444.

Each of the modules 441 to 444 of the processing capability adjusting function 440 sets the network structure for the exchange center establishment, the exchange time setting information, the processing capacity of the new exchange center to be established, and the exchange area to be included in the new exchange center. Then, the set information is transferred to the corresponding method data storage unit 530 and stored. In other words, by receiving the infrastructure function adjustment data, division equipment processing capability data, manual processing capability data and jurisdiction setting data from the user interface unit 100 to generate a load change amount for each logistics base in real time to provide the user, appropriate infrastructure processing The result of establishing the capability adjustment response plan is provided through the user screen.

Next, the operation process simulation unit 310 and the transportation process simulation unit 320 of FIG. 1 will be described with reference to FIG. 11.

11 is an exemplary view illustrating a simulation of an operation process simulation unit and a transportation process simulation unit according to an embodiment of the present invention.

As shown in FIG. 11, the operation process simulation unit 310 and the transportation process simulation unit 320 are processes for preparing distribution and distribution / distribution / distribution operations between logistics bases and logistics bases in the bases handling the logistics. Simulate about.

When the volume generation starts from the data statistical analysis function, the operation process simulation unit 310 performs a simulation by a mail type and a work condition-based process generated in the distribution points existing from the reception to the delivery process.

The letter-post is then used to generate the volume for each distribution point to be dispatched by the dispatch and distribution volume values for the destination distribution center and delivery station. To this end, the process of generating the volume for each logistics base should be included with respect to the volume of the simulation result.

The transport process simulation unit 320 starts the simulation based on the operation process result, and simulates a method of selecting and sending a transport vehicle for each destination based on a postal container conversion rate value for each postal mail and the quantity of containers that can be loaded in the transport vehicle. To do this, we simulate the transport process in the transport network. 11, the network formed between the exchange center and the central China is referred to as an exchange network, the network formed between the central office and the logistics center is called the central office network, and the network formed between the central office and the comprehensive office is called a post office network.

After the simulation of the transport process is completed, the required number of vehicles and transport costs for the transport process are calculated for each transport network, and then the simulation results are re-simulated according to the countermeasure establishment procedure to generate simulation results for comparing the countermeasures.

Next, a method of simulating an infrastructure load analysis through a system having the structure described above will be described with reference to FIG. 12.

12 is a flowchart of a method for simulating infrastructure load analysis according to an embodiment of the present invention.

As shown in Figure 12, according to an embodiment of the present invention, the operation of the infrastructure load analysis simulator for establishing and verifying the logistics infrastructure construction plan for the medium and long term according to the reference year and future quantities, the step of receiving information largely, daily basis It is a step of estimating quantity and carrying out load analysis by year.

In detail, first, the data input unit 110 of the user interface unit 100 receives the reference year or future year demand prediction data input by the user and starts the simulation (S100). At this time, the input reference year or future year demand prediction data is future by the result generated by converting the input data by base, post type, reference volume generated through the input data conversion unit 220 of the data statistical analysis unit 200 Data generated based on quantity demand forecast information.

After converting the input data to generate the input data, the daily reference quantity to be stored in the corresponding method data storage unit 530 is calculated (S110). The step S110 will be described as an example of being performed once at the beginning of the system, but is not necessarily limited thereto. When the daily reference quantity is calculated, the countermeasure establishment and result inquiry unit 130 performs a load analysis for each year based on the data (S120). At this time, the load analysis for each year is carried out for each blue or centralized station, and the preparation work for performing the simulation is completed through the step S120.

Here, a process of converting the input data by the input data converter 220 when receiving the demand prediction data in step S100 will be described with reference to FIG. 13.

13 is a flowchart illustrating an input data conversion procedure of a data converter according to an embodiment of the present invention.

As shown in FIG. 13, the input data conversion procedure includes a quantity data generation step S200, an operation / transportation reference data generation step S210, a demand prediction reference quantity generation step S220, and a future quantity generation step S230. Is done through.

Looking at each of the procedures in detail, first the volume data generation step (S200) is largely recorded mail volume data generation process, non-recorded mail volume data generation process and sending station-receiving station quantity information generation as shown in Figure 14a to 14c It can be divided into courses. 14A is a flowchart illustrating a process of generating recorded mail volume data according to an embodiment of the present invention, and FIG. 14B is a flowchart illustrating a method of generating sender-receiving station quantity information according to an embodiment of the present invention. 14C is a flowchart illustrating a process of generating unrecorded mail volume data according to an embodiment of the present invention.

In general, recorded mail generates simulation input data based on time-of-day receipt volume values. If quantity information by time of reception is not calculated, such as non-recorded mail, it is to be generated in an even distribution.

That is, as shown in FIG. 14A, the recording mail volume data generation process is based on the volume information for each reception point / type / day generated by the reception desk of the postal logistics information system. 1 quantity generation module 221-1 generates quantity information per logistics base / type / daily / time zone (S201). At this time, the volume ratio value of each time zone is generated together.

When the first quantity generation module 221-1 generates quantity information for each logistics base / type / day / time zone, the ratio value generation module 221-3 calculates the quantity for each destination country by the recipient postal code. Based on the calculation result, the input reference quantity data generation module 221-4 generates and stores from (received general administration receipt quantity) -to (delivery total administration arrival arrival quantity) quantity information (quantity and ratio value).

Here, the detailed method for generating the sending station-receiving station quantity information by the input reference quantity data generating module 221-4 is as shown in FIG. 14B. 14B is a flowchart illustrating a method of generating sending station-receiving station quantity information for a recorded mail quantity according to an embodiment of the present invention.

As shown in FIG. 14B, the input reference quantity data generation module 221-4 generates reception quantity information for each of the general office / country-based countries based on the receiving station symbol (S203-1). In this case, the received volume information by the general office / country of China is the same as the volume information generated by the reception base / type / day by the reception desk of the postal logistics information system. Then, as a result of searching for the addressee postal code in the address book recipient address serial number, the standard delivery station standard delivery quantity information is generated (S203-2).

Next, apart from the recorded mail volume data generation process mentioned in FIG. 14A of the volume data generation step S200, another non-recorded mail volume data generation process is illustrated in FIG. 14C. 14C is a flowchart illustrating a procedure of generating unrecorded mail volume data according to an embodiment of the present invention.

As shown in Fig. 14C, the quantity data extraction module 222-1 refers to the common data (ie, jurisdiction area information) in which the relationship between the logistic bases is defined, and whether the collected postal classification code is the belonging department or the central office. Identifies whether or not (S300). In this case, the post code is a code based on a receiving station identifier (for example, a registered flag, etc.) generated by the unrecorded postal receiver of the postal logistics information system for identification.

The quantity data extraction module 222-1 determines whether the collected mail type code is stored in the non-recorded mail receiving unit of the postal logistics information system (S301), thereby determining whether the non-recorded mail is a mail received from the general office of the affiliation. Or you can find out if the mail was received from your country of concentration. Then, if it is determined that the mail is not belonging to any of the general affairs bureaus or central offices, that is, if the postal code is not stored in the unrecorded mail register in the Postal Logistics Information System, then the point-by-base quantity data for the unrecorded mail. Create and store (S302).

When the volume data for each base is generated from the input reference quantity data generation module 222-2, the post type code and the reduction and additional reduction reference code values, which are preset as operation reference data for the simulation, are determined. The dividend quantity ratio generation module 222-5 generates and stores quantity information for each postal work condition and quantity ratio for each work condition (S303).

From the delivery rate ratio generation module 222-5, it is determined whether the volume information for each postal work type by day and the volume rate value data for each work condition are completed (S304). If it is completed, the simulation input data generation module 222-4 generates the shipment and the arrival destination of the country quantity (S305), and generates and stores the delivery quantity for each comprehensive country (S306).

However, if it is determined that the generation is not completed in step S304, based on the base, shipping / arrival / distribution volume value information from the operation standard volume data, the ratio value, the arrival of the central office of the central office by type of mail, and the concentration station received quantity meter value and stored (S307).

The manual generation quantity data generation module 222-3 generates and stores the shipment quantity and the ratio value for each work condition for each base, with reference to the operation management data (S308). Then, the difference value of the quantity value sent at the same time is generated, and the domestic shipment arrival classification quantity data is generated (S310).

After determining whether the creation of the delivery volume data by the general office is completed (S311), if the completion of the shipment data of each country is added, the arrival volume of the other country is added, and then the delivery volume data by the general office (or delivery station) is generated to generate information. Save (S312). However, if the result of the determination in step S311 is not completed, steps S309 and S310 are repeated until completion.

Next, the operation (S210) of generating the operation / transport reference data of FIG. 13 will be described with reference to FIGS. 15A to 15D.

15A to 15D are flowcharts illustrating an operation / transport reference data generation procedure according to an embodiment of the present invention.

In the process of generating the operation and transportation reference data, the operation and transportation reference data converter 123 is the transportation planning data, transport planning information, performance data, classification facility reference information, operation management information, machine processing, among the data of the postal logistics information system. Reference data are extracted to be used as simulation operation and transportation reference data by referring to the data related to the manual volume generation relative to the quantity (S211-1). In the embodiment of the present invention, the data of the postal logistics information system used for data extraction is as mentioned above, but is not necessarily limited thereto.

First, as shown in FIG. 15A, the work reference information generation module 233-1 determines whether reference data is extracted from the transportation plan data and the performance data among the data received from the postal logistics information system (S211-2). ). If the reference data is extracted, the fastening quantity data generation module 233-5 obtains the transport data from the reference data. For this purpose, the total number of pallets and the total number of parcels per dispatch centralized country are calculated using the reference data obtained from the fastening ledger data. It calculates (S211-5).

In addition, the fastening quantity data generation module 233-5 calculates a parcel conversion standard per pallet using the calculated total number of pallets and total number of parcels, and obtains transport rate data from the stored distance list data. Thereafter, the transportation distance fare data generation module 233-6 stores the distance fare list data obtained by obtaining the distance fare list data registered in the information storage unit 500 in the information storage unit 500 (S211-6). .

On the other hand, if it is determined in step S211-2 that the reference data has not been extracted, the manually generated quantity calculation module 233-4 extracts and registers the transport distance and fee data between bases (S211-3). After determining whether the total number of pallets and total parcels by dispatch concentration station have been calculated (S211-4), if it is determined that the total number of pallets and total parcels by dispatch concentration station have not yet been calculated, the process is performed again from step S211-1. Repeat until you have extracted the total number of pallets and total number of parcels.

Next, as shown in FIG. 15B, the classification facility reference information is used among the data received from the postal logistics information system (S212-1). The job standard information generation module 233-1 and the processing time quantity calculation module 233-2 for each time zone extract the type of facility for each base, processing capacity and classification job condition reference information, and register them in the information storage unit 500. (S212-2).

Then, in order to be able to refer to the information on the processing capacity of the division equipment in the operation reference data to be referred to by the user, the time-phase processing amount calculation module 233-2 for acquiring time-phase processing capability data The facility name, number, and processing capacity reference data for each facility are extracted from the reference data for the facility for each location, and stored in the information storage unit 500 (S212-3). It is determined whether the registration is completed in the operation standard data information storage unit 510 (S212-4), and the amount of time information for each time zone by facility is extracted until storage is completed in the information storage unit 500. Repeat after S212-1 procedure.

Next, as shown in FIG. 15C, using the operation management data among the data received from the postal logistics information system (S213-1), the reference information used for generating the sender-receiving station quantity information of the unrecorded mail is generated. To this end, the ratio value generation module 233-3 generates a ratio table using the daily volume values for shipment, arrival, and distribution for each work condition for each base in the operation management table of the postal logistics information system (S213-2). ).

Then, it is generated as a file for each base or stored in the information storage unit (S213-3). Check whether this procedure is completed (S213-4) and repeat the procedure after step S213-1 until completion.

As shown in FIG. 15D, the manual generation quantity calculation module 233-4 uses operating performance data for each base of the division facilities extracted from the operation management data of the postal logistics information system for generating the small manual quantity data (S214-1). ). After generating the small manual quantity data (S214-2) from the operating performance data for each base of the division facilities, the value of the supply quantity-division processing completion quantity is generated as the value of the manual generation rate of the corresponding base to the information storage unit 500 Save (S214-3). Then, it is checked whether the generation of the manual generation rate value among the processing supplies for each base is completed (S214-4), and the procedure after the step S214-1 is repeated until it is completed.

Next, the demand forecasting reference quantity generation step S220 and the future quantity generation step S230 of FIG. 13 will be described with reference to FIG. 16. The demand forecasting reference quantity generation step S220 and the future quantity generation step S230 illustrated in FIG. 16 illustrate a step of calculating a nationwide quantity.

16 is a flowchart illustrating generation of demand prediction reference quantity data and future quantity data according to an embodiment of the present invention.

As shown in FIG. 16, the quantity data generation module 224-1 and the reference data generation module 224-2 use the general-recorded (non-recorded) / non-recorded, specialty normal mail monthly data to track the quantity of goods by base. Quantity data is generated (S400). Then, the monthly volume data, the monthly volume data for each country, and the annual volume data for each year are generated (S410).

In the quantity change generation module 224-3, the parcels generate annual increase / decrease values according to the regression analysis results, and the type increase / decrease rate, blue CAGR value, etc. inputted from the user with reference to the generated volume and increase / decrease ratio values are described. To generate a future quantity value using (S420). At this time, the generated future volume value is generated in the form of daily volume value by category and general bureau. Then, generate the occupancy ratio value by the national quantity basis and provide it to the user (S430).

As described above, the process of transferring the quantity increase / decrease rate value for the future year is performed to the input data conversion step through the demand forecasting reference quantity generation step S220 and the future quantity generation step S230. In the input data conversion step, the daily future volume of each country is multiplied by the national volume increase / decrease input value to generate the simulation future daily volume. In addition, if the CAGP value for each blue is input, it is corrected to be equal to the sum of the quantity by the national increase rate value, and the increase / decrease rate value is generated for each future year based on the input simulation period value and the corresponding actual future year increase / decrease value value. The input data quantity reference information is corrected (S440).

At this time, the quantity reference information corrected in step S440 is the correction for the national unit of quantity. In other words, when the blue CAGR value is input, the blue value must be corrected to be equal to the sum of the quantity by the national increase rate value, and the increase / decrease value corresponding to the simulation period value and the actual future year corresponding to the input simulation period value is generated by generating the increase / decrease rate value by the future year. The input data quantity reference information should be corrected based on the rate value. For this purpose, the volume standard information should be revised together.

As a method of correcting the blue-and-white quantity reference information, the correction according to the blue-white market share or the correction based on the blue increase / decrease rate may be performed. In the embodiment of the present invention, a method of correcting the volume reference information when selecting the blue increase / decrease rate will be described as an example. Let's do it. An embodiment of correcting clear input data quantity reference information will be described with reference to FIG. 17.

17 is an exemplary diagram for correcting input data quantity reference information according to an embodiment of the present invention.

As shown in FIG. 17, from the information stored in the information storage unit 500, the input data conversion unit 220 receives the annual receipt volume for each type of mail by the fiscal year based on the detailed yearly receipt quantity for each type of mail for each reference year. To aggregate (S442). The input data conversion unit 220 multiplies the amount calculated in step S442 by a preset expression to correct the annual reception volume for each mail type (S443). At this time, the correction is repeated for the target year. In the embodiment of the present invention, the formula set in advance is "1 + competent authority CAGR x correction value t" as an example, but is not necessarily limited to this.

In this case, the annual receipt volume by mail category by reference year may require a more detailed correction of the detailed daily receipt volume by postal category by target country in more detail. Therefore, the pre-set formula used for counting the annual receipt volume by mail type by the reference year may be used to count the detailed daily receipt volume by post type by the target year.

When the data are generated as described above with reference to FIGS. 13 to 17, the procedure for verifying whether the reference data generated in step S210 is properly generated is performed. This will be described with reference to FIG. 18.

18 is a flowchart illustrating a reference data verification procedure according to an embodiment of the present invention.

As shown in FIG. 18, it is determined whether a change to the operation reference data for simulation has occurred (S500). If the operation reference data is changed, the corresponding reference data is searched and provided through the user interface unit 100 (S510). Then, after confirming the changed reference data from the user interface unit 100 (S520), after updating through the user interface and registered in the operation / transport reference data 510 (S530). This process is repeated until registration of the changed data is completed.

On the other hand, if it is determined in step S500 that the reference data for the simulation has not changed, it is determined whether to perform the simulation according to the reference year (S540). If it is determined that the simulation is to be performed (S580). On the other hand, if it is determined to wait for the simulation to be performed, that is, if the simulation start message is generated from the user interface unit, the demand prediction reference data is displayed on the user interface unit 100 (S550).

After retrieving the demand forecast value, the result is transmitted to the user interface unit 100 (S560), and when the demand forecast value is updated by the user, the changed information is stored (S570). For the demand forecasting result and the simulation period (for example, year and month), the value of the volume ratio to be communicated to the receiving bureau by time zone, distribution center working condition, and delivery bureau of the receiving volume by the general bureau is generated as the simulation input volume. Simulation is performed by the process (S580).

Next, referring to FIG. 12, when the simulation unit 300 is driven by the step S130 and the simulation is completed, the output data converter 230 receives the message that the simulation is completed from the simulation engine and uses the simulation result data. To be displayed on the interface screen. When the corresponding method establishment start message is received from the next user interface screen, it is transmitted to the corresponding method establishment unit 400, and instructs to establish a corresponding method (S140).

When the user interface unit 100 receives a message from the corresponding method establishment engine that the corresponding method is established, the user interface unit 100 displays the corresponding method establishment result data on the user interface screen. Then, the simulation unit 300 performs detailed load analysis simulation for each countermeasure to find out how much the load is when the established countermeasures are used (S150).

The simulator result data storage module 520 of the information storage unit 500 stores the comparative evaluation result of the corresponding measures, and in order to provide the corresponding information to the user, the user interface unit 100 outputs the evaluation result to the user screen. (S160). If the user interface unit 100 inputs information indicating whether or not to select a corresponding method from the user, the user interface unit 100 determines whether to complete the establishment of the corresponding method using the corresponding information (S170).

In addition, the user interface unit 100 provides comparison information for comparing the corresponding countermeasures established for each year for the overloaded bases among the simulation results (S180). Subsequently, it is determined whether the user receives the approval / appliance information informing the user to plan with the corresponding information (S190), and if it is determined that the plan is approved with the corresponding countermeasure, the infrastructure may be changed and reflected as the details. (S195). However, if it is determined that the plan is not approved as the corresponding countermeasure, the procedure after step S120 is performed.

Next, an operation flow of the operation process simulation unit 310 and the transportation process simulation unit 320 of the simulation unit 300 according to an embodiment of the present invention will be described with reference to the drawings. This is to grasp the processing capacity currently being processed in the centralized station in order to predict the future quantity and will be described with reference to FIG. 19.

19 is an exemplary view showing a queue configuration according to mail classification according to an embodiment of the present invention.

As shown in FIG. 19, when a mail quantity arrives at the central station and gets off (S600), a sending classification procedure is performed for each belonging system (S610). The finished volume is queued and transported in the arrival country's queue. At this time, the normal / special / parcel is separated to constitute a pallet (S620).

At this time, the job priority according to the shipment classification procedure performed in step S610 of FIG. 19 is as shown in FIG. 20.

20 is an exemplary diagram against work priorities in a simulation process according to an embodiment of the present invention.

As shown in FIG. 20, the shipment classification according to the embodiment of the present invention is largely divided into a small system, a large system, a special system, and a parcel system, but is not necessarily limited thereto. Small scale system is divided into mechanical processing, manual processing, and line division, and large scale system is divided into general processing and line division. The machine processing capacity uses the machine classification efficiency, and it is set as the machine processing capacity (trough / hour) by adding all the processing capacity by the unit without the unit classification by the number of division equipments.

For small machines, OVIS processing power is used for sorting out shipments, and LSM processing capacity is used for sorting out arrivals. In addition, in case of small machine, the efficiency of classification is input by reflecting the re-input rate. Re-entry rates are not considered when classifying arrivals. The type of machine processing volume is reflected by the central office, and may also reflect the use of packet separators for parcel classification.

Hand-held system is used to receive the time processing capacity (time / time) from the user interface unit 100. On the other hand, since the small line classification does not affect the system load, a certain amount of time (eg, “minutes / pallet”) is given to the line classification. At this time, all central stations apply the same time, and the same time is applied to the small and large segments.

In the case of job priorities in the sorting of shipments, the first in first out (FIFO) is processed in the order of entry without priorities. In the case of manual division, the country's quantity shall be given priority in other country's quantity because it performs large division and then detailed classification. However, when sorting arrivals, priority is not given to the task.

In the case of the quantity to be processed, the shipment category is for all items received / collected, and the arrival category included in the shipment category is also processed in the shipment category. In the small manual process, after handling all the manual work volume, the manual work generated after the machine work is processed together.

Next, when it is confirmed that the mail quantity of FIG. 19 has arrived at the logistic base, a process of generating the divided quantity in the beginning stage and configuring the same in the queue will be described with reference to FIGS. 21 and 22. . In this case, the volume of the general office is generated by the total office, in addition to the volume of the post office, the volume received from the general office. The volume of the base year is used to calculate the volume, and the zone of the year is used to carry out the simulation.

21 is an exemplary diagram illustrating a queue classification procedure for transporting from a concentrated station to a switching center according to an embodiment of the present invention, and FIG. 22 is a queue classification procedure for transporting from a switching center to a central station according to an embodiment of the present invention. It is an exemplary diagram showing.

First, as shown in FIG. 21, when the quantity of water arrived at the logistics base gets off and the finished quantity is generated (S700), a queue is formed for each destination country (S710). Thereafter, a state indicating whether delivery is determined according to a postal type and arrival time is determined (S720). Normally, shipments that arrive before the second deadline for distribution from the Arrival Convergence Bureau to the General Bureau and arrive at the General Bureau are deemed to be delivered the next day, after which they will be delivered two days later. Therefore, it is calculated that the quantity arrived before the first distribution deadline is delivered on the same day and the next day is delivered on the next day. The next day's limited express will be delivered on Saturday or Sunday.

Switching network means transport between the central office (or logistics center) and the switching center. Transportation consists of the phases of vehicle generation, vehicle loading, and vehicle departure, so that the quantity to be redistributed to the centralized country separated from the dispatch is not transported to other central offices and exchange centers. In addition, when loading a quantity of cargo, priority is given to the handling of parcels / specials.

To determine whether to go to the exchange center or the destination country, depending on the volume level, the decision is based on the size of the vehicle and the maximum number of vehicles. In the embodiment of the present invention, the size of the vehicle is described by using 11 tons, 8 tons and 5 tons as an example, but is not necessarily limited thereto.

Concentration Bureau → Exchange Center / Central China Logistics sets up a shipment (11 tons) for one Concentration Bureau to be transported directly to the Arrival Concentration Bureau. At the end of the first exchange shipment, if there is more than 10 pallets going to one central station, if it is less than 10 pallets, it is transported to the exchange center (large vehicle first, from 11 to 8 to 5 tons). .

In the case of the final vehicle to the primary exchange center, it is sent unconditionally if there is a parcel / special quantity. If there is only a regular quantity, it is temporarily stored in a queue. At the end of shipments to other central offices, it is decided to transport them directly to the destination China when the volume to a central office reaches one car (5 tons or 8 tons).

The result of the second exchange dispatch deadline is that if the volume to one concentrated country is one car (5 to 8 tons), it will be transported directly to the destination concentrated country. Carry out transportation (large vehicle first, 11 ton → 8 ton → 5 ton). Final vehicles destined for the secondary exchange center will be treated as unconditional regardless of loading rate.

On the other hand, as shown in Figure 22, in the case of exchange center-to-China transportation, if the completed exchange amount occurs (S800), after the corresponding quantity is waited by the destination country (S810), the quantity is one difference (for example) , Based on 11 tons) (S820). If the amount is one car is treated as transported (S830). At this time, the pallet configuration is divided into normal / special / parcel. The last vehicle determines the tonnage (5 tons, 8 tons) relative to the volume (S840), and the final vehicle is treated as sending unconditionally regardless of the loading rate.

Next, a procedure after establishing a countermeasure in step S140 of FIG. 12 will be described with reference to FIG. 23.

23 is a flowchart illustrating a procedure after establishment of a countermeasure scheme according to an embodiment of the present invention.

As shown in FIG. 23, when the response method established by the response method establishment unit 140 is selected by the user (S900), some or all functions of detailed response methods that need to be established among various response methods are established. Done. The function establishment procedure is largely performed as an infrastructure establishment step (S910), a jurisdiction design step (S920), a network structure design step (S930), and a processing capability adjustment step (S940).

First, the infrastructure establishment step (S910), the sorting capacity is calculated by receiving the hourly processing capacity of the sorting facilities of the new infrastructure for sending, mailing (for example, small, large, parcels, etc.) and arrival classification by mail type (for example, small, large, parcel, etc.) (S911). In order to calculate the new infrastructure processing capacity, the new infrastructure processing capacity is calculated based on a value calculated by multiplying the hourly processing power input from the user interface with the mail type of the new infrastructure and the available time for each arrival category (S912).

In addition, the normal infrastructure, parcel dispatch and arrival jurisdiction of the new infrastructure are input, and the mail classification (small, large, parcel) for each infrastructure is sent and the amount of arrival is calculated. This is to calculate the value of each category of infrastructure by performing the process of recalculating and calculating the volume of each country's mailing by infrastructure and the jurisdiction's general authority by destination as the general bureau is added to or removed from the new infrastructure.

When the calculation of the new infrastructure processing capacity (S911) and the calculation of the amount of classification for each infrastructure (S912) are completed, the load for each new infrastructure is recalculated (913S). To this end, loads for each new infrastructure are calculated by dividing each type of postal mail (small, large, parcel) sent by infrastructure and the amount classified by arrival into each processing capacity.

Next, the jurisdiction design step (S920) receives a change to the jurisdiction infrastructure for each administration, recalculate the type of mail for each infrastructure (small, large, parcel), the arrival classification (S921). To this end, as the general authority changes the current jurisdiction infrastructure for parcel delivery and arrival, the total volume of the postal administration by jurisdiction and the jurisdiction of jurisdiction by arrival is recalculated. Then, the load for each infrastructure is recalculated (S922).

The next network structure design step (S930) is performed, which receives a new exchange center, exchange time, processing capacity, and exchange zone setting data to be used as reference data for simulation of the countermeasure.

Finally, in the processing capacity adjustment step (S940), the sorting capability is recalculated by inputting a modification of the infrastructure equipment for sending and mailing by type of mail (small, large, parcel) and the hourly processing capacity of manual labor. do. Modified by infrastructure (post) by multiplying each modified time by the hourly delivery capacity of each postal mail type, arrival time by infrastructure (S941).

Then, when the function is removed due to the normalization and parcel-dedicated infrastructure of the infrastructure, or when the function is adjusted and newly established, the change of the general authority of the infrastructure jurisdiction is inputted, and the mail type (small, large, parcel) by each infrastructure is sent, and the amount of arrival is separated. When the function is added as a function of calculating, by adding or removing the general authority to the infrastructure, the amount of mails sent by infrastructure and the total authority of the competent general authority by arrival are recalculated (S942).

If the function is to be removed, the general division shall calculate the amount of infrastructure classification by re-aggregating the volume of the general administration of the regional jurisdictions by mail type and arrival by changing the current jurisdiction infrastructure for parcel shipment and arrival. (S943). In addition, the calculation of the processing capacity by infrastructure and the classification of each piece of infrastructure is performed at the same time as the calculation of the infrastructure is performed. Infrastructure processing capacity is adjusted by dividing by processing capacity.

When establishment of the countermeasures is completed according to the above procedure, detailed load analysis function can be performed by performing operation and transportation simulation using reference information on the result generated in the establishment process.

The embodiments of the present invention described above are not only implemented by the apparatus and method but may be implemented through a program for realizing the function corresponding to the configuration of the embodiment of the present invention or a recording medium on which the program is recorded, The embodiments can be easily implemented by those skilled in the art from the description of the embodiments described above.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, It belongs to the scope of right.

1 is a system structural diagram according to an embodiment of the present invention.

2 is an exemplary view showing input data generation criteria for each mail type according to an embodiment of the present invention.

3 is an exemplary diagram of a recorded mail input data converter structure of an input data converter according to an embodiment of the present invention.

4 is an exemplary diagram of an unrecorded postal input data converter structure of an input data converter according to an embodiment of the present invention.

5 is an exemplary view illustrating a structure of an operation and transport reference data converter of an input data converter according to an exemplary embodiment of the present invention.

6 is an exemplary view illustrating a demand prediction and future mail quantity generation module structure of an input data converter according to an exemplary embodiment of the present invention.

7 is a structural diagram of an output data converter according to an exemplary embodiment of the present invention.

8 is a structural diagram of an infrastructure establishment unit of a countermeasure establishment unit according to an embodiment of the present invention.

9 is a structural diagram of the jurisdiction zone design unit of the response plan establishment unit according to an embodiment of the present invention.

10 is a structural diagram of a processing capability adjusting function unit of a countermeasure establishment unit according to an embodiment of the present invention.

11 is an exemplary view illustrating an operation process simulation unit and a transportation process simulation unit according to an embodiment of the present invention.

12 is a flowchart of a method for simulating infrastructure load analysis according to an embodiment of the present invention.

13 is a flowchart illustrating an input data conversion procedure of a data converter according to an embodiment of the present invention.

14A is a flowchart for a process of generating recorded mail volume data according to an embodiment of the present invention.

14B is a flowchart illustrating a method of generating from-to quantity information according to an embodiment of the present invention.

14C is a flowchart of a process of generating unrecorded mail volume data according to an embodiment of the present invention.

15A to 15D are flowcharts illustrating an operation / transport reference data generation procedure according to an embodiment of the present invention.

16 is a flowchart illustrating generation of demand prediction reference quantity data and future quantity data according to an embodiment of the present invention.

17 is an exemplary diagram for correcting input data quantity reference information according to an embodiment of the present invention.

18 is a flowchart illustrating a reference data verification procedure according to an embodiment of the present invention.

19 is an exemplary view showing a queue configuration according to mail classification according to an embodiment of the present invention.

20 is an exemplary diagram of job priorities in a simulation process according to an embodiment of the present invention.

21 is an exemplary diagram illustrating a queue classification procedure for transport from a centralized station to a switching center according to an embodiment of the present invention.

22 is an exemplary diagram illustrating a queue division procedure for transport from a switching center to a central station according to an embodiment of the present invention.

23 is a flowchart illustrating a procedure after establishment of a countermeasure scheme according to an embodiment of the present invention.

Claims (15)

In the logistics infrastructure countermeasure simulation system, A user interface unit which receives data input from a user or provides information generated by a system; A data statistics analyzer for converting the data collected by the user interface unit into a preset format; A simulation unit for performing operations and transportation simulations based on the data output from the user interface or the converted data output from the data statistical analyzer; A countermeasure establishment unit for establishing and outputting a countermeasure according to the data output from the user interface unit; And Information storage unit for storing reference information, simulation result information and countermeasure information for simulation Simulation system comprising a. The method of claim 1, The user interface unit, A data input unit configured to collect data input from the user and transfer the collected data to the data statistical analyzer; A simulation execution and result inquiry unit which provides the user with the data collected by the data input unit or a simulation result output from the simulation unit in association with the simulation unit; And In association with the corresponding method establishing unit, establish a corresponding method based on the data collected by the data input unit or the data output from the simulation unit, and provides the corresponding method result information generated by the corresponding method establishing unit to the user Response plan establishment and result inquiry Simulation system comprising a. The method of claim 1, The data statistical analysis unit, A data migration unit for converting data output from a postal logistics information system interworking with the simulation system or data output from the user interface into a preset data form; An input data converter configured to generate a future year input quantity based on a preset demand forecast generation result required for the start of the simulation and to output the simulation result data; And An output data converter for converting simulation performance result data generated from the input data converter into output data for providing to the user Simulation system comprising a. The method of claim 3, The input data converter, Includes a recorded mail input data converter, a non-recorded mail input data converter, an operational and shipping reference data converter, and a future mail volume data converter, The record mail input data converter, A first quantity generation module for extracting and storing quantity data information for each reception point, type, and daily quantity among the data converted by the data migration unit, and generating and storing the quantity information received for each of the plurality of comprehensive countries; A second quantity generation module configured to generate and store quantity data of a dispatching general office and an arrival totaling bureau based on the received quantity information for each comprehensive country generated by the first quantity generating module; A ratio value generation module for generating shipment / arrival / distribution quantities and ratio values for each base from the information converted by the data migration unit; Upon receiving a message including arbitrary year simulation period information, arbitrary year increase rate value information, and simulation performance request information from the user interface, an input for generating input reference quantity data for each base for simulation for the arbitrary year; Reference quantity data generation module; And In case of performing the reference year simulation, the input quantity generation module which generates the input quantity data of the reference year as the simulation input quantity. Simulation system comprising a. 5. The method of claim 4, The non-recorded mail input data converter, A quantity data extraction module for extracting and storing quantity data for each work condition for each post and daily post from the data output from the postal logistics information system; A rate value generation module for generating a ratio value based on base value, shipment / arrival / distribution volume value from the data output from the postal logistics information system, and inputting first and second general offices; A manual generation quantity data generation module for generating a manual addition generation quantity data when a manual generation quantity ratio value occurs after the machine operation; A simulation input data generation module configured to generate simulation input quantity data based on an even distribution value of the reference year input quantity upon receiving simulation start information from the input reference quantity data generation module; And Receiving a request message from the user interface unit, dividend quantity ratio generation module for generating input reference quantity data for each base to perform the simulation for the future year Simulation system comprising a. 5. The method of claim 4, The operating and transportation reference data converter, A work criterion information generation module for extracting the type and processing capability of the facility and the work condition reference information for each base from the data output from the data migration unit; A processing time calculation module for each time slot that obtains processing capability data for each time zone from the data output from the data migration unit, and generates a processing time value for each time point for each base; A ratio value generation module for generating shipment / arrival / distribution quantities and ratio values for each base from the data output from the data migration unit; A manual generation quantity calculation module configured to generate a ratio value of manual quantity of manual processing to machine processing generated for each base from the data output from the data migration unit; A fastening quantity data generation module for obtaining fastening quantity data per parcel pallet from the data output from the data migration unit; And Transport distance fee data generation module for obtaining the freight rate data from the data output from the data migration unit Simulation system comprising a. 5. The method of claim 4, The future mail volume data converter, A quantity data generation module for calculating daily or monthly quantities for each base from the data output from the data migration unit; A reference data generation module for calculating quantity data for each base point by using the monthly quantity calculated by the quantity data generating module; And Volume change generation module that calculates the national average annual growth rate using the volume data from the current point in time and the newly generated standard variation value Simulation system comprising a. The method of claim 3, The output data converter, A result generation confirmation module for transmitting the simulation result and the corresponding method result outputted from the simulation unit and the corresponding method establishment unit to the information storage unit; A data retrieval module for retrieving data for each operation standard / transportation standard / volume / area stored in the information storage unit and providing the data to the user through the user interface unit; A detailed load analysis module for calculating an overload rate and daily maximum load for the logistics bases; A vehicle required calculating module for calculating a vehicle required for each transportation section and delivering the vehicle to the information storage unit; And Calculation satisfaction level calculation module for calculating mail delivery standard satisfaction rate and delivering to the information storage unit Simulation system comprising a. The method of claim 1, The simulation unit, An operation process simulation unit configured to perform simulation of operation process logic of a logistics base based on data output from the data statistical analysis unit or data output from the user interface unit; And On the basis of the results of the simulation performed in the operation simulation unit, a transport process simulation unit for performing a simulation for the transport process for transport between logistics bases Simulation system comprising a. The method of claim 1, The countermeasure establishment unit, An infrastructure establishment unit for constructing an infrastructure based on a simulation result of inputted quantity information, which is expected to occur after the current time from the outside; A jurisdiction design unit for recalculating the loads for each infrastructure by resetting the conventional and parcel jurisdictions of the already established infrastructure; A network structure design unit for designing a network structure of a simulation system and generating reference information of a simulation; And A processing power adjustment unit that recalculates the load of the infrastructure by adjusting the processing capacity of the overload infrastructure. Simulation system comprising a. The method of claim 10, The infrastructure new unit, An information collection module which receives a communication time and distance / time setting data from the user interface unit, transfers it to the information storage unit, and stores it as reference data for simulation of a corresponding scheme; An infrastructure load calculation module for calculating a quantity of each infrastructure by the information collected by the information collection module; A new infrastructure processing capability calculation module for calculating a new infrastructure processing capability from the information collected by the information collection module; And Receives information calculated by the infrastructure quantity calculation module and the new infrastructure processing capacity calculation module for each infrastructure, calculates the load for each infrastructure, and delivers the quantity classification module for each infrastructure to be delivered to the user interface unit. Simulation system comprising a. The method of claim 10, The jurisdiction design section, A setting module for receiving the normal shipping jurisdiction, the normal arrival jurisdiction, the parcel dispatch jurisdiction, and the parcel arrival jurisdiction setting information from the user interface unit; An infrastructure load estimation module for calculating an infrastructure load by changing jurisdiction data based on the reference quantity information stored in the information storage unit and the information received from the setting module; And Division quantity calculation module for each infrastructure that calculates the quantity that can be classified for each infrastructure by changing the jurisdiction data based on the reference quantity information stored in the information storage unit and the information received from the setting module Simulation system comprising a. In the way that the simulation system simulates the logistics infrastructure countermeasures, If the simulation system receives the demand forecast data for any one of the base year or any year, analyzing the load of the year based on the demand forecast data to generate load analysis information for each year; Establishing a correspondence plan for each year based on the generated load analysis information for each year by a simulation system; And The step of establishing a countermeasure by analyzing the detailed load of the countermeasures based on the yearly countermeasures established by the simulation system. Lt; / RTI > 14. The method of claim 13, Generating the load analysis information for each year, Converting the received demand forecast data into a preset format; Calculating a daily reference quantity based on the demand prediction data in which a format is converted; And Analyzing the load for each year based on the calculated daily reference quantity Lt; / RTI > The method of claim 14, The converting step, Generating postal quantity data for recorded or non-recorded postal items based on the demand forecast data, and generating quantity of delivery information based on a reference delivery country to extract quantity data; Extracting simulation operation and transportation reference data from the demand prediction data and generating the operation / transportation reference data; Generating demand daily reference data by generating daily quantity data of each base and monthly monthly quantity data; And Generating a future quantity for the arbitrary year based on the demand forecasting quantity; Lt; / RTI >

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