CN111625919B - Design method and device of logistics simulation system - Google Patents
Design method and device of logistics simulation system Download PDFInfo
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Abstract
The application discloses a design method and device of a logistics simulation system. The method comprises the following steps: acquiring site data of a website and historical data of the website; determining a correspondence between the site data, the historical data and parameters of the physical device; constructing a logistics dynamic data simulation model corresponding to the corresponding relation according to site data of the network points, historical data of the network points and parameters of the physical equipment; and optimizing a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model. According to the application, the relation between different information is established by combining the linkage conditions of the front link and the back link of the logistics and the physical equipment factors, and the key influence factors of each logistics scheme are determined through multiple tests, so that the logistics operation scheme is optimized.
Description
Technical Field
The application relates to the field of computer simulation design, in particular to a method and a device for simulating and designing logistics dynamic data.
Background
Along with the development of electronic commerce, the development of logistics industry is driven, modern people are more and more used to online shopping, express companies distribute purchased goods to designated receiving addresses, and the mailing process can finally reach clients through transportation and sorting in a plurality of links. The rapid increase of the express delivery amount requires that the processing capacity of each link of the express delivery enterprise and the increase speed of the express delivery amount are matched with each other. There are significant drawbacks to the current systems or methods adopted in the industry that are static and independent of each other.
Because the real data is variable, there are various possibilities that static data is used for analysis and research, firstly, the real system cannot be realized, the deviation between the system and the reality is large, and secondly, the static data cannot reflect some abnormal or variable states. The existing various research methods or systems are independent, the mutual influence between the linkage states of the front link and the back link and the system is ignored, the independent local optimization is realized, the system is possibly unbalanced, and the overall system performance is reduced; because the system is closed, the real running state cannot be seen, only the result can be obtained, and the reason for the result cannot be analyzed.
Therefore, how to relate the data of each link and the field device to perform the optimal design of the system or the method aiming at the existing logistics business is a problem to be solved.
Disclosure of Invention
In view of the above-mentioned drawbacks or shortcomings in the prior art, it is desirable to provide a design method and apparatus for a logistics simulation system, so as to solve the problem that the existing logistics simulation system ignores the linkage conditions of the front and rear links and the interaction between the systems.
In a first aspect, the present application provides a method for designing a logistic simulation system, the method comprising:
acquiring site data of a site and historical data of the site, wherein the site data comprises a layout diagram of the site and parameters of physical equipment in the site, and the historical data comprises information of arriving vehicles and information of on-board express mail;
determining a correspondence between the site data, the historical data, and the physical device parameters;
constructing a logistics dynamic data simulation model corresponding to the corresponding relation according to site data of the network points, historical data of the network points and parameters of the physical equipment;
and determining a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model.
Optionally, the determining the correspondence between the site data, the history data, and the parameters of the physical device includes:
determining first information according to the historical data and the site data, wherein the first information comprises vehicle arrival information, unloading information, conveying equipment information, sorting information and loading information;
determining second information according to parameters of the physical equipment, wherein the second information comprises three-dimensional image information and working performance information of the physical equipment;
and determining the corresponding relation between the second information and the first information.
Optionally, the determining a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model includes:
circularly executing the appointed operation until the optimal design of the logistics operation scheme is completed according to the simulation result;
wherein the specifying operation includes:
selecting a corresponding input value according to user operation;
keeping other input variables unchanged, and determining the performance of logistics operation under the selected input values through the simulation result of the logistics dynamic data simulation model;
checking whether the performance of the logistics operation reaches the satisfaction degree of the user;
if so, the control does not enter the next appointed operation;
if so, control proceeds to the next specified operation.
Optionally, the parameters of the physical device include:
physical parameters including the length, width, and height of the device, and performance parameters including the capacity, speed, acceleration, and deceleration of the device.
Optionally, the physical equipment is a telescopic belt conveyor, a sorting matrix, a cross belt sorting machine, a linear sorting machine, a common conveying line, a roller conveying line, a drawer machine and a small sorting cabinet.
Optionally, the method further comprises:
verifying whether the logistics dynamic data simulation model is reliable;
if not, the logistics dynamic data simulation model is corrected.
Optionally, the method further comprises:
and setting the position of the net point logistics equipment in the logistics dynamic data simulation model according to the real position of the net point logistics equipment.
Optionally, the method further comprises:
after the performance of the simulation model meets the standard, the model is tested to find out key influence factors by utilizing the monitoring and output of input parameters;
the input parameters are one or more of site data of the network points, historical data of the network points and parameters of the physical equipment.
In a second aspect, the present application also provides a design apparatus of a logistics simulation system, including:
the system comprises a data acquisition module, a storage module and a storage module, wherein the data acquisition module is used for acquiring site data of a site and historical data of the site, the site data comprises a layout diagram of the site and corresponding parameters of physical equipment in the site, and the historical data comprises information of arriving vehicles and information of on-board express items;
a relationship determination module configured to determine a correspondence between the site data, the history data, and parameters of the physical device;
the model construction module is configured to construct a logistics dynamic data simulation model corresponding to the corresponding relation according to the site data of the network points, the historical data of the network points and the parameters of the physical equipment;
and the data optimization module is configured to determine a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model.
Optionally, the relationship determination module includes:
a first information determining unit configured to determine first information including vehicle arrival information, unloading information, conveying equipment information, sorting information, and loading information according to the history data and the site data;
and the second information determining unit is configured to determine three-dimensional image information and working performance information of the physical equipment according to the parameters of the physical equipment.
And a relationship determination unit configured to determine a correspondence relationship between the second information and the first information.
The embodiment of the application has the beneficial effects that: in the prior art, the operation conditions of all links in an express enterprise are researched by using a simulation platform, but the linkage operation states of the front link and the rear link and the influence among all the operations are not considered, only the local optimization of logistics operation is independently researched, and the problems of equipment, flow sequence, personnel configuration and the like are not comprehensively analyzed. According to the scheme, a corresponding logistics dynamic data simulation model is established by combining site data of the mesh points, historical data of the mesh points and equipment parameters; and establishing the relation among different information, and determining key influence factors of each logistics scheme through multiple experiments, so as to optimize the logistics operation scheme.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of a design method of a logistic simulation system according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for determining correspondence between site data and historical data of a network point and parameters of a physical device according to an embodiment of the present application;
FIG. 3 is an exemplary flow chart of designated operations of an embodiment of the application;
FIG. 4 is an exemplary flow chart of a logistic simulation system model modification step according to an embodiment of the present application;
FIG. 5 is a schematic diagram of a design device of a logistic simulation system according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a computer system of a server according to an embodiment of the present application.
Detailed Description
The application is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be noted that, for convenience of description, only the portions related to the application are shown in the drawings.
The dynamic data simulation analysis platform is utilized to study the conditions of all links in the express enterprise, the real and reliable operation effect can be reflected, the method is an advanced scientific method, the simulation system simulates the operation of a real system through detailed and accurate control, and the result and the generated reason of the system can be rapidly and intuitively analyzed. Firstly, a simulation model corresponding to a real system is constructed by abstracting and systemizing a real study object, and the bottleneck and improvement method of the model system are found by analyzing and researching the simulation model. And finally, the improved method is applied to the real system, so that the aim of improving the real system through the research of a simulation model is fulfilled. The dynamic data simulation analysis platform mainly comprises the following aspects that firstly, the dynamic property of input data, such as the arrival time of a vehicle, the number, the size, the weight and other information of on-board express items, is scientifically set according to the result of probability statistics; secondly, the dynamic property of the model process, the simulation analysis platform dynamically displays the running state of the system through a visual interface; thirdly, the dynamics of the output result is realized, a simulation analysis platform is applied, a plurality of groups of parameters can be arranged and combined, a plurality of groups of experimental designs are carried out, the system carries out comprehensive judgment according to a plurality of selected indexes, and the most suitable scheme is selected.
As mentioned in the background art, the increasing speed of the express delivery is high at the present stage, the processing capacity of each link of the express delivery enterprise is required to keep up with the increasing speed of the express delivery, the increasing requirement of the service can be met only if the processing capacity of each link is improved, the processing capacity of each link is improved rapidly, and the problem to be solved is how to reasonably and systematically evaluate and feed back the existing express delivery links. The current industry adopts static and independent systems or methods to study, and has obvious defects.
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
The method of the embodiment of the present application will be described below with reference to flowcharts.
In a first aspect, an embodiment of the present application provides a method for designing a logistic simulation system. Fig. 1 shows a method flow diagram of a design method of a logistics simulation system according to an embodiment of the present application. The method comprises the following steps:
step S11, site data of the sites and historical data of the sites are obtained, the site data comprises a layout diagram of the sites and parameters of physical equipment in the sites, and the historical data comprises information of arriving vehicles and information of on-board express items.
Specifically, site data of sites and historical data of sites are collected, wherein the sites comprise sites such as transfer stations and storage bins, the site data comprise layout diagrams of sites and parameters of physical equipment in the sites, and the historical data comprise historical vehicle data, historical express mail information, historical personnel information and historical equipment configuration information. The layout diagram of the site can be referred to herein as a CAD drawing, from which many data can be reflected, such as information on the positions of walls and columns, the positions of channels, the placement positions of equipment, and the like in the CAD drawing of the building facility; the parameters of the physical device include parameters of the transport device such as length, width, speed, acceleration, deceleration, and parameters of the transport device such as number of devices, capacity of the devices, speed, acceleration, deceleration, etc. The vehicle arrival information mainly comprises vehicle type, reversing time information of the vehicle, quantity and weight information of cargoes carried by the vehicle and the like; the information of the express mail mainly comprises the type, length, width, height and other size information of the express mail, weight information of the express mail, destination flow direction information of the express mail and the like.
Furthermore, the data are cleaned and arranged through a data processing tool such as Excel and SQL database software, and useless redundant data are screened out; inputting useful data into an experifit data fitting device, and fitting the tidied data; selecting a fitting function with the highest score from the fitting function groups by comparison as the fitting function of the group of data; and finally, the fitting function is used as an input parameter to be sent into a simulation model to be constructed, and the dynamic data simulation of the simulation model is carried out.
Step S12, determining correspondence between site data, history data, and parameters of the physical device.
Specifically, the site data of the acquired sites include site shift information, vehicle arrival information, express mail information, conveying equipment information, sorting plan information and loading information. The sorting plan information comprises sorting plans of different stations, including matrix sorting, loading sorting and small piece sorting; the express mail information comprises different types of express mail, and the proportion of different destinations corresponds to different moments. In addition, the three-dimensional appearance of the physical equipment is determined according to the main appearance structure of the three-dimensional image information display equipment in the acquired physical equipment parameters, and the working performance of the physical equipment is determined. And determining the distribution relation of the quantity of the express items passing through each device of the site in time according to the site data of the network points, the historical data of the network points and the physical devices under each service model.
It can be understood that the correspondence between the three herein determines the location of the physical device on site and the speed of transporting the express item for the parameters of the logistics device; the site information comprises shift information, sorting plans and the like, and the information needs to be embodied on physical equipment, namely, the information of logistics equipment is consistent with the information of the site along with time change; the historical data information is mainly the operation data of the site, which is directly expressed on the physical equipment as the number of pieces flowing through the equipment with time.
And S13, constructing a logistics dynamic data simulation model corresponding to the corresponding relation according to site data of the mesh points, historical data of the mesh points and parameters of the physical equipment.
Specifically, a three-dimensional model of the equipment is built according to physical properties of the equipment such as length, width and height, performance properties of the equipment such as speed, acceleration and deceleration, and the like, a main appearance structure of the equipment is displayed, and based on site data of the network points, historical data of the network points and parameters of the physical equipment, the three-dimensional appearance of a logistics equipment object can be changed through deep secondary development, and the function of the logistics equipment object is edited through C++ language or a Flexscript language of software.
It will be appreciated that for each device development, the device labels must be set based on the device attributes, such as the length, width, height, and working time of the field staff of the matrix module, etc. parameters are defined by adding labels, and the corresponding parts of the simulation model can be changed by reading the values of the labels through commands. The simulation model can enable parameters which are required to be modified commonly to be changed through the addition of a custom interface, the model is changed through the input of data on the custom interface, then the edited equipment model is added into a user library, and a corresponding file is exported to complete the development of a module library. When in use, the simulation of the site can be completed by importing the module library and then simply editing and modifying.
Furthermore, the device function part of the simulation model can be developed according to the on-site operation flow and sorting mode, such as a matrix sorting mode, wherein the on-site staff sorts the fast-moving parts with fixed flow directions to corresponding sliding grooves, and the specific implementation mode of the logic is as follows: firstly, defining the current object, the express mail, the conveying line and the express delivery attribute on the conveying line, and selecting a specific logistics scheme of the express mail next. Because the express mail has a destination attribute, when the express mail passes through the matrix position, the matrix operator needs to determine whether the code of the passing express mail belongs to the destination set of the loading area corresponding to the current matrix. And if the express mail is in the current set destination set and the state of the operator is idle, sorting and placing the current express mail in a corresponding sorting chute. After the operation is finished, the operation information of the current operator needs to be updated in time, wherein the operation information mainly comprises the sorted number, the checked number and the missed number. After all the operations are completed, the status information of the operator is changed so as to perform the operation of the next express item. The writing of codes and corresponding text interpretation are performed based on the above business modes, and are input into a system of a simulation model.
It can be understood that different operation procedures are developed and set according to site data of the sites, history data of the sites and parameters of physical equipment by combining the operation flow of the sites in the logistics. For example, in the unpacking link, unpacking the express mail, decomposing the express mail into small pieces with different numbers according to different ticket-package ratios, and after the specific development of different procedures, associating the previous and subsequent procedures according to a specific linking mode, such as S-link or A-link, so that the express mail can be transported according to the set procedure, and the above setting can be used for improving and adding the functionality in the simulation model.
And S14, determining a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model.
Specifically, according to the input data, the real-time output result is observed, the model supports the real-time graph display of the result data, and the running state of the system is displayed in real time by utilizing three-dimensional display. The model input data is historical statistics data, the actual current state is reflected by probability statistics according to the historical data, and different attributes of each vehicle are endowed according to the probability, such as the vehicle size, the vehicle arrival time and the number of express items on the vehicle; for the passing probability of the express mail, attributes of the express mail, such as flow direction information, size information, weight information and the like, are given, and simulation of different logistics schemes is performed by carrying out variation of the data. According to the operation efficiency of each link under each logistics scheme, the design of the logistics scheme is optimized according to the efficiency change of the net points or the intermediate transfer express. It can be understood that under the condition that a certain input variable is kept unchanged, the input variable is continuously adjusted or changed, the functional relation between the selected original setting parameter and the job sorting efficiency is determined according to the simulation result of the obtained simulation model, and the optimal value of the selected original setting parameter or the human efficiency under the logistics scheme equipment is determined according to the functional relation.
Optionally, determining the correspondence between the site data of the mesh point, the history data of the mesh point, and the parameters of the physical device includes:
fig. 2 is a flow chart of a method for determining correspondence between site data and history data of a network point and parameters of a physical device according to an embodiment of the present application.
Step S121, determining first information according to the history data and the site data, wherein the first information includes vehicle arrival information, unloading information, conveying equipment information, sorting information and loading information.
Specifically, the production of the vehicle is determined according to the collected historical data and site data of the network points, wherein the production comprises loading vehicle information and unloading vehicle information, and the loading vehicle information and the unloading vehicle information comprise corresponding express mail information on the vehicle; the unloading information mainly refers to queuing of vehicles, reversing of vehicles and unloading of express items, the conveying equipment information refers to conveying and transferring of the express items from one position to another position, the sorting information refers to carrying out various rough sorting or subdivision on the express items according to the destination, the type and other attributes of the express items, and the loading information refers to carrying out final sorting, scanning and loading on the express items according to loading flow directions.
Step S122, determining second information according to the parameters of the physical equipment, wherein the second information comprises three-dimensional image information and working performance information of the physical equipment.
Specifically, the three-dimensional image information of the physical equipment is used for truly restoring the real scene of the field through the three-dimensional appearance of the image, so that the equipment is more vivid; the working performance information refers to the working efficiency and the equipment performance of the physical equipment under the appointed logistics scheme.
Step S123, determining a correspondence between the second information and the first information.
Specifically, after determining the input information parameters of the model, further mining the correlation between the variables is required, so as to better define the simulation model.
Further, the embodiment of the application provides specific steps of the designating operation in the design method of the logistics simulation system, and fig. 3 shows an exemplary flowchart for circularly executing the designating operation.
In step S14, if the specified operation is performed in a loop, the design is completed until the optimal design of the logistics operation scheme is completed according to the simulation result.
Wherein the specifying operation includes:
step S141, selecting corresponding input values according to user operation;
step S142, keeping other input variables unchanged, and determining the performance of logistics operation under the selected input values through the simulation result of the logistics dynamic data simulation model;
step S143, checking whether the performance of the logistics operation reaches the satisfaction degree of the user;
if so, the control does not enter the next appointed operation;
if so, control proceeds to the next specified operation.
Specifically, each user performs sensitivity research on input parameters of each logistics scheme, namely sensitivity analysis can be performed according to parameters which the user wants to research, one input equipment parameter or one system parameter is selected, and parameters closely related to output results are determined by researching the influence of the parameters on the output results, so that site operation is optimized in a targeted manner.
Optionally, the parameters of the physical device include: physical parameters including length, width, and height of the device, and performance parameters including capacity, speed, acceleration, and deceleration of the device.
Specifically, the physical device in the embodiment of the application can set the parameters of the device according to the requirement of actual logistics operation. The physical device parameters in the embodiment of the application refer to physical parameters and performance parameters, and the length, width and height of the device are physical parameters of the device, and it should be noted that the type of the parameters is just an example, and other parameters exist, such as position, size, turning radius, ascending height, descending height, linear speed and acceleration of a flowing water section, etc.; capacity, speed, acceleration, deceleration are performance parameters of the device.
Further, for example, the sorting device has a pocket and a bag collecting frame, wherein the pocket and the bag collecting frame are used for outputting final express items, and the bag collecting bag is sleeved on the pocket and is used for accommodating express items falling from the pocket. The number and size of the lattice openings in the sorting equipment are also physical parameters, so that the physical equipment parameters include parameters reflecting the physical properties and the working performance of the physical equipment parameters, and the embodiment of the application is not particularly limited.
Optionally, the physical equipment is a telescopic belt conveyor, a sorting matrix, a cross-belt sorter, a linear sorter, a common conveyor line, a roller conveyor line, a drawer machine and a small sorting cabinet.
Specifically, in addition to the above, the physical equipment in the embodiment of the application further comprises a common conveying line, a roller conveying line, a telescopic belt conveyor, a drawer machine, a bag supply table, a sorting cabinet, a security inspection machine, a static scale, a dynamic scale, a bar code scanner and the like. The sorting matrix mainly comprises a first matrix and a second matrix in the logistics industry, wherein the first matrix is a sorting mode of sorting from one flow direction to two flow directions and the second matrix is a sorting mode of sorting from one flow direction to four flow directions.
On the basis of the above embodiment, the method further includes:
verifying whether the logistics dynamic data simulation model is reliable; if not, the logistics dynamic data simulation model is modified.
Specifically, the reliability of the model is mainly verified through the multiple disc of the historical data, firstly, historical information of vehicles and express items is input into the model, the unloading completion time, the loading completion time, the number of processed express items and the like are output, then the model is compared with the historical data, and through multiple tests, if the deviation between the data output by the model and the historical data is within a certain range, the design of the model can be confirmed to be reliable. Setting a standard, which is adjustable, and which is set according to the size and complexity of the research system, after the model is identified and adjusted beyond this range, for example, in some embodiments, a fixed value study may be performed, where the deviation rate of the output data of the simulation model from the real data is less than or equal to 5%.
It can be understood that the correction process mainly includes statistical analysis through equipment and personnel data in the simulation model design, including output and utilization rate, and comparison with the actual condition on site, if there is a large difference, performing on-line inspection and modification on the functional code of each process, gradually perfecting the functional structure of each process from the previous process to the last process, so that the on-site condition can be accurately reflected.
Further, the steps of correcting the logistics dynamic data simulation model are as shown in fig. 4: firstly, running a built simulation model, and carrying out statistics output on data of equipment and personnel; step two, analyzing the output data, and comparing and analyzing the output data with the data collected in the actual field; thirdly, if the difference of the comparison results is large, the model is not perfect enough, the functional codes and parameters of each station are checked to see whether the deviation from the actual is large, and the station with the problem is found out; step four, modifying the function codes or parameters of the problematic stations; step five: and running the model again, and carrying out statistical analysis on the data again until the deviation between the model output data and the actual data is within an acceptable degree.
Optionally, the method further comprises:
and setting the position of the net point logistics equipment in the logistics dynamic data simulation model according to the real position of the net point logistics equipment.
Specifically, different proportions of settings can be performed, and the embodiment of the application adopts one-to-one setting of the physical equipment on the simulation platform according to the actual position, so that the simulation model is closer to reality. For example, the position of the device, the length of the device, the width of the device, and also the remaining parameters of the device, such as the speed of the input device.
Optionally, the method further comprises:
after the performance of the simulation model meets the standard, the model is tested to find out key influence factors by utilizing the monitoring and output of input parameters;
the input parameters are one or more of site data of the mesh point, historical data of the mesh point and parameters of the physical equipment.
Specifically, the key parameters are parameters with the largest influence factors on the scheme in the input parameters, namely the key influence factors in the embodiment of the application. The key parameters are core data in the field data, such as unloading completion time, loading completion time, the number of processed express items, personnel use data and the like. After multiple tests, key influence factors under different schemes are selected, the result under each scheme is output, and key input parameter indexes such as loading completion time and processed information quantity are selected. The simulation system comprehensively compares the output results of each scheme, selects the scheme which has the least investment of resource allocation (manpower/equipment) and the like and can meet the production requirement, namely the optimal scheme. For example, 4 experimental factors are set, the values of the factors are different, a plurality of groups of experiments are formed, a coordinate horizontal axis represents different experimental scenes of input, a vertical axis represents key parameters of output, and a scheme meeting target aging requirements is finally selected through comparison of different experimental results.
In a second aspect, the present application further provides a design device of the logistics simulation system, and fig. 5 is a schematic structural diagram of the design device of the logistics simulation system. As shown, the apparatus 20 includes:
the data acquisition module 21 is configured to acquire site data of the sites and history data of the sites, wherein the site data comprises a layout diagram of the sites and corresponding parameters of physical equipment in the sites, and the history data comprises information of arriving vehicles and information of on-board express items;
a relationship determination module 22 configured to determine correspondence between site data, historical data, and parameters of the physical device;
the model construction module 23 is configured to construct a logistic dynamic data simulation model corresponding to the corresponding relation according to site data of the mesh points, historical data of the mesh points and parameters of the physical equipment;
the data optimization module 24 is configured to determine a logistics operation scheme according to a simulation result of the logistics dynamic data simulation model.
Referring to fig. 5, in some embodiments, the relationship determination module 22 further includes:
a first information determining unit 221 configured to determine first information including vehicle arrival information, unloading information, conveying apparatus information, sorting information, and loading information, based on the history data and the site data;
a second information determining unit 222 configured to determine three-dimensional image information and operation performance information of the physical device according to the parameters of the physical device;
a relationship determination unit 223 configured to determine a correspondence relationship between the second information and the first information.
It should be understood that the subsystems or units described in the apparatus correspond to the respective steps in the method described with reference to fig. 1-2, and thus, the operations and features described above for the method are equally applicable to the apparatus and the units contained therein, and are not repeated herein.
Referring now to FIG. 6, there is illustrated a schematic diagram of a computer device 600 suitable for use in implementing embodiments of the present application.
As shown in fig. 6, the computer device 600 includes a Central Processing Unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present disclosure, the process described above with reference to fig. 1 may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the method of fig. 1. In such embodiments, the computer program may be downloaded and installed from a network via a communication portion, and/or installed from a removable medium. The above-described functions defined in the system of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 601.
The computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules involved in the embodiments of the present application may be implemented in software or in hardware. The described units or modules may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases. The described units or modules may also be provided in a processor, for example, as: a processor comprises a data acquisition module, a relation determination module, a model construction module and a data optimization module. The names of these units or modules do not in any way limit the units or modules themselves, and the data acquisition module may also be described as "configured to acquire site data of a site including a layout of the site, corresponding parameters of physical devices in the site, and history data of the site including information of arrival vehicles, information of on-board express items", for example.
As another aspect, the present application also provides a computer-readable medium that may be contained in the electronic device described in the above embodiment; or may exist alone without being incorporated into the electronic device. The computer-readable medium carries one or more programs which, when executed by one of the electronic devices, cause the electronic device to implement the method of theme transformation of the electronic device as described in the above embodiments.
For example, as shown in fig. 1, the electronic device may implement, in step 11, acquiring site data of a site and historical data of the site, where the site data includes a layout diagram of the site and parameters of physical devices in the site, and the historical data includes information of arrival at a vehicle and information of a express mail on the vehicle; step 12, determining the corresponding relation among site data, historical data and physical equipment parameters; step 13, constructing a logistics dynamic data simulation model corresponding to the corresponding relation according to site data of the mesh points, historical data of the mesh points and parameters of the physical equipment; and step 14, determining a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model.
It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit in accordance with the disclosed embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order or that all illustrated steps be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware.
Claims (8)
1. A method for designing a logistic simulation system, comprising:
acquiring site data of a site and historical data of the site, wherein the site data comprises a layout diagram of the site and parameters of physical equipment in the site, and the historical data comprises information of arriving vehicles and information of on-board express mail;
determining a correspondence between the site data, the historical data, and the physical device parameters;
constructing a logistics dynamic data simulation model corresponding to the corresponding relation according to site data of the network points, historical data of the network points and parameters of the physical equipment;
determining a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model;
wherein the determining the correspondence between the site data, the history data, and the physical device parameter includes:
determining first information according to the historical data and the site data, wherein the first information comprises vehicle arrival information, unloading information, conveying equipment information, sorting information and loading information;
determining second information according to parameters of the physical equipment, wherein the second information comprises three-dimensional image information and working performance information of the physical equipment;
and determining the corresponding relation between the second information and the first information.
2. The method according to claim 1, wherein determining a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model comprises:
circularly executing the appointed operation until the optimal design of the logistics operation scheme is completed according to the simulation result;
wherein the specifying operation includes:
selecting a corresponding input value according to user operation;
keeping other input variables unchanged, and determining the performance of logistics operation under the selected input values through the simulation result of the logistics dynamic data simulation model;
checking whether the performance of the logistics operation reaches the satisfaction degree of the user;
if so, the control does not enter the next appointed operation;
if so, control proceeds to the next specified operation.
3. The method of claim 1, wherein the parameters of the physical device comprise:
physical parameters including the length, width, and height of the device, and performance parameters including the capacity, speed, acceleration, and deceleration of the device.
4. The method of claim 1, wherein the physical devices are telescopic belt conveyors, sorting matrices, cross-belt sorters, straight sorters, common conveyor lines, roller conveyor lines, drawer machines, and small sorting cabinets.
5. The method as recited in claim 1, further comprising:
verifying whether the logistics dynamic data simulation model is reliable;
if not, the logistics dynamic data simulation model is corrected.
6. The method as recited in claim 1, further comprising:
and setting the position of the net point logistics equipment in the logistics dynamic data simulation model according to the real position of the net point logistics equipment.
7. The method as recited in claim 1, further comprising:
after the performance of the simulation model meets the standard, the model is tested to find out key influence factors by utilizing the monitoring and output of input parameters;
the input parameters are one or more of site data of the network points, historical data of the network points and parameters of the physical equipment.
8. A design apparatus for a logistic simulation system, comprising:
the system comprises a data acquisition module, a storage module and a storage module, wherein the data acquisition module is used for acquiring site data of a site and historical data of the site, the site data comprises a layout diagram of the site and corresponding parameters of physical equipment in the site, and the historical data comprises information of arriving vehicles and information of on-board express items;
a relationship determination module configured to determine a correspondence between the site data, the history data, and parameters of the physical device;
the model construction module is configured to construct a logistics dynamic data simulation model corresponding to the corresponding relation according to the site data of the network points, the historical data of the network points and the parameters of the physical equipment;
the data optimization module is configured to determine a logistics operation scheme according to the simulation result of the logistics dynamic data simulation model;
the relationship determination module further includes:
a first information determining unit configured to determine first information including vehicle arrival information, unloading information, conveying equipment information, sorting information, and loading information according to the history data and the site data;
a second information determining unit configured to determine three-dimensional image information and working performance information of the physical device according to parameters of the physical device;
and a relationship determination unit configured to determine a correspondence relationship between the second information and the first information.
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| CN112596413B (en) * | 2020-12-14 | 2022-11-29 | 昆船智能技术股份有限公司 | Simulation test system and method for control program of cigarette sorting system |
| EP4064158A1 (en) * | 2021-03-22 | 2022-09-28 | Tata Consultancy Services Limited | Method and system for dynamically optimizing the operations of logistics management system |
| CN112926162B (en) * | 2021-04-01 | 2023-06-23 | 广东三维家信息科技有限公司 | Electric control drill connection control optimization method and device, electronic equipment and storage medium |
| CN116150946B (en) * | 2022-11-17 | 2023-09-22 | 北京东方通科技股份有限公司 | Pipeline arrangement method based on simulation technology |
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