KR102644670B1 - Method for providing transportation management system - Google Patents

Abstract

In accordance with some embodiments of the present disclosure, a method for providing a transportation management system performed by a server including at least one processor is disclosed. The method includes obtaining first history information about the transportation history of a shipper requesting transportation service for a predetermined period of time; Determining a vehicle supply and demand plan through the vehicle supply and demand algorithm by inputting second history information and the first history information about the existing transportation history processed by the transportation management system into the vehicle supply and demand algorithm; determining a first transportation cost for operating a fixed vehicle to which a predetermined transportation quantity is pre-allocated from the vehicle supply and demand plan; calculating a second transportation cost for operating a non-fixed vehicle to handle transportation items not handled by the fixed vehicle from the vehicle supply and demand plan; and generating a bid proposal based on the first transportation cost and the second transportation cost.

Description

{METHOD FOR PROVIDING TRANSPORTATION MANAGEMENT SYSTEM}

The present disclosure relates to a method for providing a transportation management system, and more specifically, to a transportation management system that provides recommended information about a freight rate proposed by a transportation company to a shipper based on the transportation history of the shipper over a predetermined period of time.

RFP (Request For Proposal) is a term used in the transportation industry that can refer to a request for proposal sent by a shipper to multiple transportation companies. Here, the shipper may be a company or person who wishes to request transportation of cargo, and the transport company may be a company that transports the shipper's cargo. Such a request for proposal may include information about the cargo or constraints related to the transportation of the cargo.

Representatives of transportation companies that have received a request for proposal can create a bid proposal based on the information included in the request for proposal. The bid proposal may include information on the unit price for transporting the cargo or the plan for transporting the cargo. Transportation company representatives may spend a lot of time and effort writing bid proposals to conclude a contract with a shipper.

However, transportation companies may have difficulty creating a reasonable bid proposal because the information included in the request for proposal is somewhat limited, sometimes the request for proposal is received with a short submission deadline, or the person in charge is short of manpower. Since shippers decide which transport company to contract with based on the contents of the bid proposal received from transport companies, if the content of the bid proposal is inadequate, they may not contract with the transport company that delivered the bid proposal.

Republic of Korea Open Patent 10-2019-0019599

This disclosure has been devised in response to the above-described background technology, and seeks to provide a method for providing a transportation management system capable of creating a reasonable bid proposal.

The technical problems of the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the description below.

According to an embodiment of the present disclosure for solving the problems described above, a method for providing a transportation management system performed by a server including at least one processor is disclosed. The method includes obtaining first history information about the transportation history of a shipper requesting transportation service for a predetermined period of time; Determining a vehicle supply and demand plan through the vehicle supply and demand algorithm by inputting second history information and the first history information about the existing transportation history processed by the transportation management system into the vehicle supply and demand algorithm; determining a first transportation cost for operating a fixed vehicle to which a predetermined transportation quantity is pre-allocated from the vehicle supply and demand plan; calculating a second transportation cost for operating a non-fixed vehicle to handle transportation items not handled by the fixed vehicle from the vehicle supply and demand plan; Based on the first transport cost and the second transport cost, generating a bid proposal - the bid proposal produces a transport quote determined based on the first transport cost and the second transport cost, the transport quote It may include - including transportation quotation calculation information indicating the basis and the vehicle supply and demand plan;

The first history information includes a plurality of transportation items, and each of the plurality of transportation items may include parameters for transportation conditions.

The parameters for the transportation conditions may include at least one of shipper characteristics, cargo type, cargo weight, origin, destination, departure time, arrival time, tonnage of the vehicle used for transportation, and type of vehicle used for transportation.

Determining the vehicle supply and demand plan may include performing a vehicle dispatch simulation for transportation items included in the first history information; grouping transportation items included in the first history information into a plurality of first sub-history groups based on a plurality of sub-periods; grouping transportation items included in the second history information into a plurality of second sub-history groups based on the plurality of sub-periods; By merging the information of the first sub-history group and the information of the second sub-history group for each of the plurality of sub-periods based on the plurality of first sub-history groups and the plurality of second sub-history groups, a plurality of Creating merge history groups of; determining fixed vehicle supply and demand information applicable to all sub-periods based on the plurality of merged history groups; And it may include determining supply and demand information for a non-fixed vehicle based on the fixed vehicle supply and demand information.

The step of determining the vehicle supply and demand plan includes analyzing transportation routes of transportation items to which each of the vehicles set as the fixed vehicles is assigned based on supply and demand information of the fixed vehicle; Among the vehicles set as fixed vehicles, if at least one of the origin and destination is repeated more than a predetermined standard number of times in the transportation routes of transportation items assigned to the fixed vehicle, the fixed vehicle is replaced with an untitled vehicle whose entire fare is predetermined. and determining a portion of the fare to be transferred to one of the predetermined finished vehicles; And among the vehicles set as fixed vehicles, if the number of repetitions of the origin and destination in the transportation routes of transportation items assigned to the fixed vehicle is less than a predetermined standard number, the fare for the fixed vehicle is determined by the transportation sales. It may include the step of deciding on a sales-based vehicle.

The performing a vehicle dispatch simulation for the transportation items included in the first history information may include: performing a vehicle dispatch simulation based on transportation conditions of the transportation items included in the first history information; A first rationalization step to determine cost savings according to the morning dispatch ratio and afternoon dispatch ratio of vehicles, a second rationalization step to optimize base transportation visits, and between transportation items included in the first history information and the second history information. It may include a step of adjusting the vehicle dispatch simulation results through a third rationalization step of reviewing whether or not double transport or combined transport is required.

Determining whether there is a candidate transport item that can be combined with transport items included in the second history information among transport items included in the first history information to determine whether the combined transport is performed; When combining the candidate transportation items with transportation items included in the second history information, determining whether an increase in vehicle tonnage is necessary; It can be determined by comparing the freight rate before upgrading the tonnage of the vehicle and the freight rate after increasing the tonnage of the vehicle.

Determining the second transportation cost may include extracting parameter sets for transportation conditions of transportation items expected to be processed by the non-stationary vehicle from the first history information; determining expected transportation costs by inputting at least some of the combinations of parameter sets of transportation items expected to be handled by the non-stationary vehicle into an artificial neural network; and determining the second transport cost based on the expected transport costs and statistical information about a distribution of parameter sets for transport conditions of transport items expected to be handled by the non-stationary vehicle. .

In another aspect, a server for providing a transportation management system is disclosed. The launched server includes a communication department; and a processor controlling a communication unit, wherein the processor acquires first history information about the transportation history of a shipper requesting transportation service for a predetermined period of time; Determining a vehicle supply and demand plan through the vehicle supply and demand algorithm by inputting second history information and the first history information about the existing transportation history processed by the transportation management system into the vehicle supply and demand algorithm; determining a first transportation cost for operating a fixed vehicle to which a predetermined transportation quantity is pre-allocated from the vehicle supply and demand plan; calculating a second transportation cost for operating a non-fixed vehicle to handle transportation items not handled by the fixed vehicle from the vehicle supply and demand plan; Based on the first transport cost and the second transport cost, generating a bid proposal - the bid proposal produces a transport quote determined based on the first transport cost and the second transport cost, the transport quote Including transportation quotation calculation information indicating the basis for the vehicle and the vehicle supply and demand plan - can be performed.

The technical solutions obtainable from this disclosure are not limited to the solutions mentioned above, and other solutions not mentioned above will be clearly apparent to those skilled in the art from the description below. It will be understandable.

This disclosure has been devised in response to the above-described background technology, and seeks to provide a method for providing a transportation management system capable of creating a reasonable bid proposal.

The effects that can be obtained from the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below. .

Various aspects will now be described with reference to the drawings, where like reference numerals are used to collectively refer to like elements. In the examples below, for purposes of explanation, numerous specific details are set forth to provide a comprehensive understanding of one or more aspects. However, it will be clear that such aspect(s) may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form to facilitate describing one or more aspects.
1 illustrates an example system for performing a method for providing a transportation management system in accordance with some embodiments of the present disclosure.
2 is a flowchart illustrating an example of a method for providing a transportation management system according to some embodiments of the present disclosure.
FIG. 3 is a diagram illustrating an exemplary schema of first history information.
Figure 4 is a flow chart illustrating the process of performing step S120 shown in Figure 3.
Figure 5 is a diagram illustrating an exemplary vehicle supply and demand plan determined based on first history information.
FIG. 6 is a conceptual diagram illustrating a process by which the server 100 determines a fixed vehicle according to an exemplary embodiment.
FIG. 7 is a flowchart illustrating an example of a process in which the dispatch simulation process shown in step S121 of FIG. 4 is advanced.
Figure 8 is a flowchart illustrating the process of performing step S140 of Figure 2.
Figure 9 is a conceptual diagram showing a process in which a server determines the transportation cost of a non-stationary vehicle by inputting the first to fifth parameter sets into an artificial neural network.

Since the present invention can make various changes and have various embodiments, specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all changes, equivalents, and substitutes included in the spirit and technical scope of the present invention. While describing each drawing, similar reference numerals are used for similar components.

Terms such as first, second, A, B, etc. may be used to describe various components, but the components should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, a first component may be named a second component, and similarly, the second component may also be named a first component without departing from the scope of the present invention. The term and/or includes any of a plurality of related stated items or a combination of a plurality of related stated items.

When a component is said to be "connected" or "connected" to another component, it is understood that it may be directly connected to or connected to the other component, but that other components may exist in between. It should be. On the other hand, when it is mentioned that a component is “directly connected” or “directly connected” to another component, it should be understood that there are no other components in between.

The terms used in this application are only used to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the technical field to which the present invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and unless explicitly defined in the present application, should not be interpreted in an ideal or excessively formal sense. No.

In the present disclosure, the server may obtain first history information about the shipper's transportation history for a predetermined period of time. For example, the first history information may include information about transportation items requested by the shipper from transporters over a period of one year. An administrator providing a transportation management system can receive information about transportation items for one year from the shipper. The manager may process information on transportation items received from the shipper to create first history information and input it into the server. Through this, the server can obtain first history information.

The server may determine a vehicle supply and demand plan using the first history information and the second history information. Based on the first history information and the second history information, the server can predict the total transportation volume that must be digested in the future when the transportation management system accepts the shipment volume of the shipper. If the server accepts additional transportation volume from the shipper to the transportation volume it was previously managing, it can predict the transportation volume that will need to be handled in the future. For example, the server may predict the amount of transportation that must be transported over a predetermined period of time based on first history information and second history information accumulated over a predetermined period of time. The server can determine the supply and demand plan for vehicles needed to handle the corresponding transportation volume. In this process, the server can determine the operation plan for fixed vehicles and the operation plan for non-fixed vehicles. Here, the fixed vehicle may mean a vehicle for which a certain amount of transportation has been allocated in advance by contract. Fixed vehicles are untitled vehicles for which the transportation fares are all determined by contract in advance, and except for some items such as fuel costs, toll fees, and fuel costs, the remaining items (e.g., vehicle depreciation costs, labor costs, meal expenses, etc.) in the transportation fares are determined in advance by contract. It can be divided into finished vehicles contracted for and sales-based vehicles whose transportation freight is determined depending on sales to the customer at the time of transportation.

Additionally, a non-fixed vehicle may refer to a vehicle that is assigned and contracted for each transportation item to handle excess transportation volume in addition to the transportation volume digested by fixed vehicles.

Once the vehicle supply and demand plan is determined, the server may determine a first transportation cost for fixed vehicle operation and a second transportation cost for non-fixed vehicle operation. The server may generate or support the creation of a bid proposal based on the first transportation cost and the second transportation cost. The server may generate or support the creation of a bid proposal by considering the first and second transportation costs and additional revenue.

The server may deliver the determined transportation quotation to the person in charge of the transportation company to help the person in charge create a bid proposal, or directly create a bid proposal based on the transportation quotation. Hereinafter, a method for providing a transportation management system according to the present disclosure will be described through FIGS. 1 to 9.

1 illustrates an example system for performing a method for providing a transportation management system according to some embodiments of the present disclosure.

Referring to FIG. 1, the server 100 may include a processor 110, a storage unit 120, and a communication unit 130. However, the above-described components are not essential for implementing the server 100, so the server 100 may have more or less components than the components listed above.

Server 100 may include any type of computer system or computer device, such as, for example, a microprocessor, mainframe computer, digital processor, portable device, or device controller.

Server 100 may include typical computer hardware (e.g., a device that may include a computer processor, memory, storage, input and output devices, and other components of a traditional computing device; electronic communications devices such as routers, switches, etc.; network attachments) A combination of electronic information storage systems (such as network-attached storage (NAS) and storage area network (SAN)) and computer software (i.e., instructions that cause a computing device to function in a particular way). This can be used to achieve desired system performance.

In the present disclosure, the server 100 may be understood as a computing device operated by a transportation company. The transport company may be a company that transports the shipper's cargo. As another example, the server 100 may be understood as a computing device operated by a company that prepares a bid proposal for transportation fares on behalf of a transport company or provides information necessary to prepare a bid proposal.

The processor 110 can typically process the overall operation of the server 100. The processor 110 processes signals, data, information, etc. input or output through the components of the server 100 or runs an application program stored in the storage unit 120, providing or processing appropriate information or functions to the user. can do.

The processor 110 may consist of one or more cores, such as a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), a tensor processing unit (TPU), etc. It may include a processor for data analysis.

In the present disclosure, the processor 110 generates a bid proposal or outputs information necessary for generating a bid proposal based on the obtained first history information and the second history information for transportation items previously managed by the transportation management system. can do.

Specifically, the processor 110 may predict the total transportation volume when receiving additional transportation volume from a shipper in the future based on the first history information and the second history information and determine a vehicle supply and demand plan for this. The processor 110 may determine the first transportation cost required for fixed vehicle operation and the second transportation cost required for non-fixed vehicle operation based on the vehicle supply and demand plan. The processor 110 may generate a bid proposal based on the first transportation cost and the second transportation cost or output information necessary for generating a bid proposal.

Hereinafter, an example of a method by which the processor 110 generates a bid proposal will be described with reference to FIG. 2.

Storage unit 120 may include memory and/or persistent storage media. Memory is a flash memory type, hard disk type, multimedia card micro type, card type memory (e.g. SD or XD memory, etc.), and RAM (Random Access). Memory, RAM), SRAM (Static Random Access Memory), ROM (Read-Only Memory, ROM), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk, optical disk It may include at least one type of storage medium.

The communication unit 130 may include one or more modules that enable communication between the server 100 and the communication system, between the server 100 and the shipper terminal 200, or between the server 100 and the network 300. there is.

The shipper terminal 200 may include a personal computer (PC), a notebook (note book), a mobile terminal, a smart phone, a tablet PC, etc. owned by the shipper. It can include all types of terminals that can access wired/wireless networks. Alternatively, the shipper terminal 200 may include typical computer hardware (e.g., a device that may include a computer processor, memory, storage, input and output devices, and other components of a conventional computing device; electronic communication devices such as routers, switches, etc.); electronic information storage systems (such as network-attached storage (NAS) and storage area networks (SANs)) and computer software (i.e., instructions that cause a computing device to function in a certain way) A combination may be used to achieve desired system performance.

In the present disclosure, the shipper terminal 200 may transmit information about the shipper's transportation history to the server 100 or another computing device of the manager who manages the server 100. Information about the shipper's transportation history may correspond to the first history information described above. The server 100 may process information about the shipper's transportation history on its own to generate first history information. As another example, the server 100 may receive first history information processed from the shipper's transportation history information by the administrator of the server 100.

The network 300 may be a closed network such as a Local Area Network (LAN) or a Wide Area Network (WAN), or an open network such as the Internet. The Internet uses the TCP/IP protocol and several services that exist at its upper layer, such as HTTP (Hyper Text Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), and SNMP. It refers to a worldwide open computer network structure that provides (Simple Network Management Protocol), NFS (Network File Service), and NIS (Network Information Service).

Below, a specific method by which the server 100 provides the transportation management system will be described.

2 is a flowchart illustrating an example of a method for providing a transportation management system according to some embodiments of the present disclosure.

Referring to FIG. 2, the server 100 may obtain first history information. The first history information may include information about the shipper's transportation history for a predetermined period of time. For example, the manager of the server 100 may receive information about transportation history for a predetermined period (eg, one year) from the shipper and process the information to generate first history information. The server 100 may obtain first history information based on the administrator's input data. As another example, the server 100 may acquire first history information by processing information about the shipper's transportation history for a predetermined period on its own.

The first history information may be information about the shipper's transportation history during a predetermined period processed to fit a predetermined format. For example, the first history information may include a plurality of transportation items. A plurality of transportation items may correspond to details requested by the shipper for transportation during a predetermined period of time. Each of the plurality of transport items may include parameters for transport conditions.

FIG. 3 is a diagram illustrating an exemplary schema of first history information.

Referring to FIG. 3, first history information may include a plurality of transportation items. Each of the plurality of transport items may correspond to each row of the table shown in FIG. 3. A plurality of transport items may correspond to transport orders requested by the shipper over a predetermined period of time in the past. For example, transportation orders requested by a shipper over the past year may correspond to transportation items.

Each of the transport items may include parameters for transport conditions. For example, parameters for transportation conditions may include shipper characteristics, cargo type, cargo weight, origin, destination, departure time, arrival time, tonnage of the vehicle used for transportation, type of vehicle used for transportation, etc. .

Column C1 represents parameters for shipper characteristics. Parameters for shipper characteristics may be determined considering the shipper's industry. Based on the shipper's industry, parameters for the shipper's characteristics may be determined as one of the predetermined categories. For example, parameters for shipper characteristics may be determined according to a standard industrial classification code or one of codes independently determined by the manager of the server 100. Column C2 represents parameters for cargo type. The cargo type may be determined as one of the cargo type categories pre-entered into the server 100. The shipper characteristic parameters and cargo type parameters may be considered when the server 100 determines the type, tonnage, etc. of vehicles allocated to the shipper's transportation items when determining a vehicle supply and demand plan, which will be described later. For example, depending on the characteristics of the shipper and the type of cargo, the types and tonnage levels of vehicles available when distributing vehicles for transportation items may be set differently.

Column C3 represents parameters for cargo weight. The cargo weight parameter may be recorded as the actual cargo weight, or the tonnage category closest to the actual cargo weight among the categories for the predetermined tonnage may be recorded. Columns C4 and C5 represent parameters for the transportation origin and destination, and columns C6 and C7 represent parameters for the departure time and disembarkation time. Parameters for the origin and destination can be processed and input to enable the server 100 to conveniently calculate a transportation route, which will be described later. For example, the origin and destination can be entered in standard street name address or legal district code format.

Column C8 represents parameters for tonnage information of the vehicle dispatched for the corresponding transportation item. Column C9 represents parameters for information on the type of vehicle that has been dispatched for the corresponding transportation item. The tonnage and type information of the vehicle may be categorized into one of predetermined categories. The tonnage of the vehicle and the type of vehicle may be determined based on information on the vehicle used in actual transportation, or may be determined differently from the information on the vehicle used in actual transportation at the request of the shipper.

As shown in FIG. 3, the first history information may include information about transportation items included in the shipper's transportation history recorded according to a predetermined format. The server 100 may store the first history information in the DB. The server 100 may store first history information and second history information in the DB. The second history information may include information about transportation history that was previously managed by the transportation management system for a predetermined period of time. As shown in FIG. 3, the second history information may include information about previously managed transportation items in the same format as the first history information.

Referring again to FIG. 3, in step S120, the server 100 may determine a vehicle supply and demand plan based on the first history information and the second history information. The server 100 may determine a vehicle supply and demand plan by inputting first history information and second history information into the vehicle supply and demand algorithm.

FIG. 4 is a flowchart illustrating the process of performing step S120 shown in FIG. 3.

Referring to FIG. 4, in step S121, the server 100 may perform a vehicle dispatch simulation for each transportation item included in the first history information. Since the second history information includes transportation items previously managed by the transportation management system, vehicle dispatch information for each transportation item may be stored in advance. Accordingly, the server 100 may simulate the dispatch of vehicles for the transportation items included in the first history information, taking into account the situation of additionally receiving orders for the transportation items included in the first history information.

The server 100 may simulate vehicle dispatch by considering transportation conditions included in transportation items. The server 100 can filter vehicles that can be dispatched for the corresponding transportation item by considering cargo type, cargo weight, vehicle tonnage, and vehicle type. The server 100 may determine which owner's vehicle to assign the transportation item to by considering information on the origin and destination among the transportation conditions and the origin and destination preferred by the owner of the vehicle. Additionally, the server 100 can prevent different transportation items that are carried out in the same time zone from being assigned to the same vehicle owner based on the departure time and disembarkation time.

Figure 5 is a diagram illustrating an exemplary vehicle supply and demand plan determined based on first history information.

Referring to FIG. 5, the vehicle supply and demand plan may include a C10 column indicating identification information on the dispatched vehicle for each transport item, and a C11 column indicating the tonnage of the dispatched vehicle for each transport item. The server 100 can simulate vehicle allocation for each transportation item by performing step S121 of FIG. 4 . Information on the C10 column and C11 column can be determined by performing step S121.

Referring again to FIG. 4, in step S122, the server 100 may determine a fixed vehicle and a non-fixed vehicle.

The server 100 stores transportation items included in the first history information (for example, including transportation items requested by the shipper over the past year) in a plurality of sub-periods (for example, the sub-periods are divided by month). can be grouped into a plurality of first sub-history groups based on (determined). Similarly, the server 100 divides transportation items included in the second history information (for example, including transportation items processed by the transportation management system over the past year) into a plurality of second sub periods based on a plurality of sub periods. You can group into history groups.

FIG. 6 is a conceptual diagram illustrating a process by which the server 100 determines a fixed vehicle according to an exemplary embodiment.

Referring to FIG. 6, the server 100 may group transportation items included in first history information into a plurality of first sub-history groups. For example, the server 100 may group transport items processed in last January into the A1 group among transport items included in the first history information. Additionally, the server 100 may group transport items processed in February among transport items included in the first history information into group A2. Likewise, the server 100 may divide transportation items included in the second history information by month and group them into B1 group, B2 group, B3 group, etc.

The server 100 may create a merged history group by merging the first sub history group and the second sub history group grouped by each sub period (eg, month). For example, the server 100 may merge the A1 group and the B1 group to extract information about the total transportation volume expected in January when receiving the shipper's transportation volume in the future. Similarly, the server 100 may merge the A2 group and the B2 group to extract information about the total transportation volume expected in February when receiving the shipper's transportation volume in the future. The server 100 may determine the total expected transportation volume for each sub-section (eg, per month).

The server 100 may check information on vehicles assigned based on vehicle simulation results for the merge history group corresponding to each of the sub-sections. For example, the server 100 may extract information on vehicles to which transportation items are assigned a predetermined number of times (for example, 18 times per month) or more for the same vehicle each month.

The server 100 may determine the number of vehicles that perform more than a predetermined number of transportation orders per month. For example, the server 100 may determine the quantity of fixed vehicles based on the average quantity of vehicles that perform transport orders more than a predetermined number of times per month. The server 100 can determine the quantity of fixed vehicles by vehicle type and tonnage level.

As another example, the server 100 may check the month in which the number of vehicles performing transport orders more than a predetermined number of times is minimum for each vehicle type and tonnage level. The server 100 may determine the quantity of vehicles that perform exercise orders more than a predetermined number of times in a given month as the quantity of fixed vehicles corresponding to the corresponding vehicle type and tonnage level.

The method for determining the quantity of a fixed vehicle described above is merely an example, and the specific method for determining the quantity of a fixed vehicle may be changed to the extent that a person skilled in the art can easily change it.

The server 100 may allocate remaining transportation items to non-stationary vehicles, excluding transportation items allocated to fixed vehicles each month.

Referring again to FIG. 4, server 100 may further determine a detailed classification of the stationary vehicle. The server 100 may extract transportation items assigned to each of the vehicles set as fixed vehicles. The server 100 may classify vehicles among fixed vehicles to which transportation items with the same starting point on the transportation route are assigned more than a standard number of times as untitled vehicles or finished vehicles. As another example, the server 100 may classify vehicles among fixed vehicles to which transportation items with the same destination on the transportation route are assigned more than a standard number of times as untitled vehicles or finished vehicles.

An untitled vehicle may refer to a vehicle for which the freight fee for the vehicle has been fixedly set in advance. For example, a fixed freight fee may be paid on a monthly basis for a vehicle classified as an untitled vehicle by the server 100. The server 100 may classify vehicles that repeatedly process transportation items with the same origin and destination, that is, vehicles that repeatedly transport a predetermined section as untitled vehicles, among fixed vehicles. The server 100 can simplify future fare contract procedures by determining fares in advance for owners of vehicles that repeatedly travel a specific section. Additionally, the server 100 can more effectively and accurately predict the cost of processing the shipper's transportation volume by classifying some of the fixed vehicles as untitled vehicles.

A finished vehicle may refer to a vehicle for which some items of the freight fee for the vehicle have been fixedly set in advance. For example, for vehicles classified as finished vehicles by the server 100, excluding some items such as fuel costs, toll costs, and fuel costs, the remaining items (e.g., vehicle depreciation costs, labor costs, meal expenses, etc.) are included in the transportation fare. It can be decided in advance by contract. The server 100 may set a vehicle that processes transportation items with the same origin more than a predetermined number of times as a finished vehicle among fixed vehicles. The server 100 may set different repetition count standards for classifying a vehicle as an untitled vehicle and a repetition count standard for determining a finished vehicle. For example, the server 100 may set the repetition number standard for classifying a vehicle as a finished vehicle to be lower than the repetition number standard for classifying it as an untitled vehicle. Through this, the server 100 can support determining in advance some items of fares for vehicles that repeatedly use the same origin or destination among vehicles that are not classified as untitled vehicles. Through this, the server 100 can simplify the freight fee settlement process for future finished vehicles and more effectively and accurately predict the cost of processing the shipper's transportation volume.

The server 100 may determine vehicles that do not satisfy the conditions of untitled vehicles and finished vehicles among fixed vehicles as sales-based vehicles. For sales vehicles, freight rates may be determined for each transportation item depending on the cargo transportation contract with the shipper. For example, the freight fee for a sales-based vehicle may be determined as the amount of sales to the shipper minus a predetermined commission.

The vehicle supply and demand plan determined by the server 100 may be stored in the DB. Referring to FIG. 5, the vehicle supply and demand plan may be stored in the C10 column, C11 column, C12 column, and C13 column. In column C12, information indicating whether the vehicle assigned to each transportation item is a fixed vehicle or a non-fixed vehicle can be stored. In column C13, information indicating detailed classification of fixed vehicles may be stored.

The process in which dispatch simulation is performed in step S121 of FIG. 4 has been explained. The dispatch simulation may initially be performed by filtering based on transport conditions. Afterwards, the dispatch simulation can go through an advancement process.

FIG. 7 is a flowchart illustrating an example of a process in which the dispatch simulation process shown in step S121 of FIG. 4 is advanced.

In step S121-a of FIG. 7, the server 100 may adjust the dispatch simulation result by considering cost reduction according to the morning dispatch ratio and afternoon dispatch ratio of vehicles. To help understand the explanation of cost savings according to the morning dispatch ratio and afternoon dispatch ratio of vehicles, please refer to Table 1 below.

Past dispatch information Second rationalization result arrive
standard Morning dispatch ratio Afternoon dispatch rate total freight arrive
standard Morning dispatch ratio Afternoon dispatch rate total freight day 80% 20% 300,000 won day 90% 10% 270,000 won day 100% 0% 250,000 won

In Table 1, past dispatch information may be extracted from past transportation order information similar to the current transportation order information determined from processor 110. Referring to past dispatch information, the morning dispatch ratio may have been set at 80% and the afternoon dispatch ratio at 20% in order to transport cargo similar to the first cargo. Accordingly, the total freight charge may have been 300,000 won.

The server 100 may determine a rationalization plan based on the morning dispatch ratio and afternoon dispatch ratio of vehicles. If the morning dispatch ratio of vehicles for transporting the first cargo is set to 90% and the afternoon dispatch ratio is set to 10%, it can be predicted that a freight rate of 270,000 won will be incurred. If the morning dispatch ratio of the vehicle for transporting the first cargo is set to 100% and the afternoon dispatch ratio is set to 0%, it can be predicted that a freight charge of 250,000 won will be incurred. However, depending on the vehicle supply and demand plan, there may be cases where the morning dispatch ratio cannot be set to 100%. Accordingly, the server 100 can determine the morning dispatch ratio and afternoon dispatch ratio that can reduce the cost of processing certain transportation items.

In step S121-b, the server 100 may adjust the vehicle dispatch simulation results to optimize the base transportation visit. Here, a hub can be understood as a place for transportation, transfer, transshipment, unloading, or loading of cargo.

In step S121-c, the server 100 may determine whether there is cargo for the shipper that can be transported in double cargo or combined transport. Here, double cargo transportation can be understood as transportation in which a vehicle transports cargo to a destination and then returns with another cargo when returning from the destination to the starting point. Combined transportation can be understood as transportation in which two or more cargoes whose destinations are the same or nearby from the point of origin or near the point of origin are loaded into one vehicle and delivered to the destination. Therefore, when there is cargo that can be transported by double cargo or combined transport, making the most of double cargo transport or combined transport may be a way for the transport company to reduce the cost of transporting the cargo. Alternatively, it may be a plan that allows the transport company to receive payment for multiple items with one transport.

Determining whether there is a candidate transport item that can be combined with the transport items included in the second history information among the transport items included in the first history information to determine whether the combined transport is performed, selecting the candidate transport item in the second history information When combined with the transportation items included in, the step of determining whether an increase in the tonnage of the vehicle is necessary, and the step of comparing the freight rate before raising the tonnage of the vehicle with the freight rate after increasing the tonnage of the vehicle. It can be decided by

Accordingly, the server 100 can determine whether double cargo or combined cargo exists. Through the above-described rationalization processes, the server 100 can improve the vehicle dispatch simulation results.

Referring again to FIG. 2, in step S130, the server 100 may determine a first transportation cost for operating a fixed vehicle. The transportation cost of an untitled vehicle among fixed vehicles can be determined based on the transportation volume expected to be handled by the untitled vehicle. Among fixed vehicles, the transportation cost of a finished vehicle may be determined based on the time of transportation of transportation items expected to be digested by the finished vehicle and expected oil price information at the time of transportation. The oil price prediction information may be determined based on future oil price prediction information rather than past oil price information stored in the first history information and the second history information. The server 100 may access an external database or obtain future oil price prediction information based on an oil price prediction model entered by an administrator. The server 100 may determine the transportation cost of the finished vehicle based on future oil price prediction information and the transportation route of each transportation item handled by the finished vehicle. The server 100 may determine the transportation cost of the sales-based vehicle based on the expected sales of transportation items handled by the sales-based vehicle. The server 100 may determine the first transportation cost based on the transportation costs of untitled vehicles, finished vehicles, and sales vehicles.

In step S140, the server 100 may determine a second transportation cost for operating a non-stationary vehicle. A non-fixed vehicle is a vehicle that has not been contracted in advance and may be a vehicle that is temporarily contracted to handle volumes exceeding the volume digested by fixed vehicles. Therefore, predicting fares for non-stationary vehicles may be more difficult than predicting fares for fixed vehicles.

Figure 8 is a flow chart illustrating the process of performing step S140 of Figure 2.

A variety of factors can be considered in determining fares for non-stationary vehicles. In step S141, the server 100 may extract transportation items expected to be processed by a non-stationary vehicle from the first history information. The server 100 may extract parameter sets for predicting transportation costs from the transportation conditions of each transportation item expected to be handled by a non-stationary vehicle. For example, server 100 may extract a first parameter set for a transportation order from transportation conditions. The first parameter set may include information on the type of cargo, cargo loading and unloading point, cargo weight, etc. for each transport item. The server 100 may extract second to fifth parameter sets based on transportation conditions, weather prediction information, and oil price prediction information.

The second parameter set may include parameters for weather information.

Specifically, the second parameter set may include at least one parameter of the average temperature on the date of transportation of the transportation item handled by the non-stationary vehicle, wind speed at the loading and unloading location, and precipitation at the loading and unloading location on that date. You can. The server 100 assumes that transportation items processed by non-stationary vehicles among the first history information will be processed under the same conditions on the same date in the future, and determines a second parameter set using expected weather information at that time in the future. You can. The server 100 may determine the second parameter set using a model that determines weather information based on accumulated data related to past weather.

The third parameter set may include parameters for the legal equivalent code.

Specifically, the third parameter set may include at least one parameter among the legal local code of the loading address and the legal local code of the unloading address. Here, the legal district code may be a code assigned on an administrative district basis. Legal neighborhood codes can be provided through the Ministry of Public Administration and Security's administrative standard code management system. Depending on the embodiment, the third parameter set may include parameters for the administrative district code.

The fourth parameter set may include parameters for oil price information.

The server 100 may access an external database or obtain future oil price prediction information based on an oil price prediction model entered by an administrator. The server 100 assumes that transportation items processed by non-stationary vehicles among the first history information will be processed under the same conditions on the same date in the future, and determines the fourth parameter set using the expected oil price information at that time in the future. You can.

The fifth parameter set may include information about the distance between loading and unloading locations. The distance of the route that provides the shortest transportation time from the loading and unloading point, the shortest distance from the loading and unloading point, the taxi fare for the route corresponding to the distance from the loading and unloading point to the above-mentioned loading and unloading point, and It may include at least one of the straight-line distances to the drop-off point.

In step S142, the server 100 of the server 100 may input a combination of parameter sets extracted from each of the transportation items processed by the non-stationary vehicle into an artificial neural network to determine the transportation cost of the corresponding transportation item.

FIG. 9 is a conceptual diagram illustrating a process in which the server 100 determines the transportation cost of a non-stationary vehicle by inputting the first to fifth parameter sets into an artificial neural network. Parameter set combination 1, Parameter set combination 2,?? Each parameter set combination may correspond to at least one transport item among transport items handled by the non-stationary vehicle.

The processor 110 can determine the transportation cost for transporting the shipper's cargo by inputting it into a pre-trained artificial neural network. The artificial neural network may be a network model based on Convolutional Neural Networks (CNN), Artificial Neural Network (ANN), Deep Neural Network (DNN), support vector machine (SVM), LightGBM, RandomForest, or Recurrent Neural Network (RNN). An artificial neural network may be a network model that outputs transportation costs when at least a predetermined set of parameters is input.

Referring again to FIG. 8, in step S143, the server 100 may determine the second transportation cost based on the output of the artificial neural network. For example, the server 100 may determine the transportation cost of each of all transportation items handled by a non-stationary vehicle using an artificial neural network and determine the second transportation cost based on this. As another example, the server 100 may output transportation costs by inputting combinations of parameter sets extracted from some of the transportation items processed by non-stationary vehicles into an artificial neural network. Server 100 may determine a statistical distribution of parameter set combinations extracted from transportation items processed by a non-stationary vehicle to determine the transportation cost of the entire non-stationary vehicle, including some of the above items and other items. The server 100 may determine the second transportation cost by inputting combinations of parameter sets extracted from some items into an artificial neural network using statistical distribution of parameter set combinations and assigning weights to the transportation costs.

Referring again to FIG. 2, in step S150, the server 100 may output information for generating a bid proposal based on the first transportation cost and the second transportation cost. As another example, the server 100 may generate and output the bid proposal itself.

A method of providing a transportation management system for a server according to exemplary embodiments has been described above with reference to FIGS. 1 to 9 . According to at least one embodiment, when the server receives the shipper's transportation volume in the future from first history information based on the shipper's transportation history, a vehicle supply and demand plan for the entire volume to be processed in the transportation management system may be determined. According to at least one embodiment, when the server accepts the shipper's transportation volume based on the first history information and the second history information, the supply and demand plan for fixed vehicles and non-fixed vehicles is reasonably determined, so that in the future vehicle supply and demand process Necessary contract procedures can be simplified. In addition, through pre-allocation of fixed vehicles, the costs required for vehicle supply and demand can be reduced and the costs required to process the shipper's volume can be predicted. According to at least one embodiment, the server may determine a transportation cost for a non-stationary vehicle using an artificial neural network. According to at least one embodiment, the server may easily provide information necessary for generating a bid proposal for a transportation freight rate to a shipper.

The description of the presented embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Thus, the present disclosure is not limited to the embodiments presented herein but is to be interpreted in the broadest scope consistent with the principles and novel features presented herein.

Claims (9)

1. A method for generating a bid proposal performed by a server comprising at least one processor, comprising:
Obtaining first history information about a first transportation history for a predetermined period of time of a shipper requesting transportation service;
When the transportation management system accepts additional transportation volume of the shipper from the existing transportation history by inputting the second history information and the first history information about the existing transportation history processed by the transportation management system into the vehicle supply and demand algorithm. , estimating the total transportation volume during the predetermined period and determining a vehicle supply and demand plan for the total transportation volume during the predetermined period through the vehicle supply and demand algorithm - the vehicle supply and demand plan includes the total transportation volume during the predetermined period Includes fixed vehicle supply and demand information and non-fixed vehicle supply and demand information for processing - ;
determining a first transportation cost for operating a fixed vehicle to which a predetermined transportation quantity is pre-allocated from the vehicle supply and demand plan;
calculating a second transportation cost for operating a non-fixed vehicle for handling transportation items not handled by the fixed vehicle among the total transportation volume for the predetermined period from the vehicle supply and demand plan; and
Based on the first transport cost and the second transport cost, generating a bid proposal - the bid proposal produces a transport quote determined based on the first transport cost and the second transport cost, the transport quote - Includes transport quotation calculation information indicating the basis for the above vehicle supply and demand plan;
Including,
The step of determining the vehicle supply and demand plan is,
performing vehicle dispatch simulation for transportation items included in the first history information;
grouping transportation items included in the first history information into a plurality of first sub-history groups based on a plurality of sub-periods;
grouping transportation items included in the second history information into a plurality of second sub-history groups based on the plurality of sub-periods;
By merging the information of the first sub-history group and the information of the second sub-history group for each of the plurality of sub-periods based on the plurality of first sub-history groups and the plurality of second sub-history groups, a plurality of Creating merge history groups of;
determining fixed vehicle supply and demand information applicable to all sub-periods based on the plurality of merged history groups; and
determining supply and demand information for a non-fixed vehicle based on the fixed vehicle supply and demand information;
Including,
method.
According to claim 1,
The first history information includes a plurality of transportation items,
Each of the plurality of transport items includes parameters for transport conditions,
method.
According to claim 2,
The parameters for the above transport conditions are
Containing at least one of shipper characteristics, cargo type, cargo weight, origin, destination, departure time, arrival time, tonnage of the vehicle used for transportation, and type of vehicle used for transportation,
method.
delete According to claim 1,
The step of determining the vehicle supply and demand plan is,
Analyzing transportation routes of transportation items assigned to each of the vehicles set as the fixed vehicles, based on supply and demand information of the fixed vehicle;
Among the vehicles set as the fixed vehicle, if at least one of the origin and destination is repeated more than a predetermined standard number of times in the transportation routes of the transportation items assigned to the fixed vehicle, the fixed vehicle is determined to be one of the untitled vehicle and the finished vehicle. Step - The untitled vehicle is a vehicle whose entire fare is determined in advance, and the finished vehicle is a vehicle whose fare is partially determined in advance -; and
Among the vehicles set as fixed vehicles, if the number of repetitions of the origin and destination in the transportation routes of transportation items assigned to the fixed vehicle is less than a predetermined standard number, the fare for the fixed vehicle is determined by the transportation sales. Step of determining a sales system vehicle - For the sales system vehicle, the fare is determined by the corresponding transportation sales -;
Including,
method.
delete delete delete A server that generates a bid proposal,
Ministry of Communications; And a processor that controls the communication unit, wherein the processor
Obtaining first history information about a first transportation history for a predetermined period of time of a shipper requesting transportation service;
When the transportation management system accepts additional transportation volume of the shipper from the existing transportation history by inputting the second history information and the first history information about the existing transportation history processed by the transportation management system into the vehicle supply and demand algorithm. , estimating the total transportation volume during the predetermined period and determining a vehicle supply and demand plan for the total transportation volume through the vehicle supply and demand algorithm;
determining a first transportation cost for operating a fixed vehicle to which a predetermined transportation quantity is pre-allocated from the vehicle supply and demand plan;
calculating a second transportation cost for operating a non-fixed vehicle to handle transportation items not handled by the fixed vehicle from the vehicle supply and demand plan; and
Based on the first transport cost and the second transport cost, generating a bid proposal - the bid proposal produces a transport quote determined based on the first transport cost and the second transport cost, the transport quote - Includes transport quotation calculation information indicating the basis for the above vehicle supply and demand plan;
Do this,
The step of determining the vehicle supply and demand plan is,
performing vehicle dispatch simulation for transportation items included in the first history information;
grouping transportation items included in the first history information into a plurality of first sub-history groups based on a plurality of sub-periods;
grouping transportation items included in the second history information into a plurality of second sub-history groups based on the plurality of sub-periods;
By merging the information of the first sub-history group and the information of the second sub-history group for each of the plurality of sub-periods based on the plurality of first sub-history groups and the plurality of second sub-history groups, a plurality of Creating merge history groups of;
determining fixed vehicle supply and demand information applicable to all sub-periods based on the plurality of merged history groups; and
determining supply and demand information for a non-fixed vehicle based on the fixed vehicle supply and demand information;
To perform,
server.