CN115700672A - Cargo transportation mode determining method, device, equipment and storage medium - Google Patents
Cargo transportation mode determining method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN115700672A CN115700672A CN202110857347.8A CN202110857347A CN115700672A CN 115700672 A CN115700672 A CN 115700672A CN 202110857347 A CN202110857347 A CN 202110857347A CN 115700672 A CN115700672 A CN 115700672A
- Authority
- CN
- China
- Prior art keywords
- cargo
- transportation
- target
- freight
- parameters
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides a cargo transportation mode determining method, a cargo transportation mode determining device, cargo transportation equipment and a storage medium, wherein the cargo transportation mode determining method comprises the following steps: acquiring goods operation information of target goods in a current supply chain network; acquiring goods transportation parameters of target goods in the supply chain network; determining a plurality of goods supply and demand parameters of the target goods according to the goods operation information, the goods transportation parameters and preset goods transportation constraint conditions; and determining the cargo transportation mode of the target cargo from a plurality of cargo transportation modes according to the plurality of cargo supply and demand parameters. The method and the device are based on production and marketing balance, can be suitable for supply chain optimization under various scenes, combine the relation between supply and demand and the relation between transportation modes, determine the most appropriate target cargo transportation mode, optimize the cost of the supply chain and improve the efficiency of cargo transportation.
Description
Technical Field
The application relates to the technical field of communication, in particular to a method and a device for determining a cargo transportation mode of a supply chain, computer equipment and a storage medium.
Background
In supply chain management optimization, production and marketing balance refers to optimization of matching relationship between production capacity of factories in different positions and customer requirements in different positions. With the development of logistics and information flow technologies, the scale of a supply chain is larger and larger, a supply and demand network covers the whole country, a plurality of SKUs are cooperatively supplied, and the optimization difficulty of supply and demand relations is larger and larger, which is embodied in the following aspects: first, the supply chain supply-demand relationship is no longer 1 to 1 or 1 to many, but many to many. Due to wide coverage and strong randomness of the demand, the cross-region supply is correspondingly increased; secondly, the subdivision of the logistics transportation products is more obvious, the application range, the cost and the timeliness of different logistics transportation modes are different, and the cost calculation of supply and demand matching is influenced; finally, the scale of supply and demand matching is increased, the types of scenes are increased, and a universal method is lacked to support balance optimization of production and marketing in various scenes.
Disclosure of Invention
The application provides a method and a device for determining a goods transportation mode of a supply chain, computer equipment and a storage medium, which are used for determining the most appropriate target goods transportation mode, optimizing the cost of the supply chain and improving the goods transportation efficiency.
According to an aspect of the present application, there is provided a cargo transportation mode determination method, characterized in that the method includes:
acquiring goods operation information of target goods in a current supply chain network;
acquiring goods transportation parameters of target goods in the supply chain network;
determining a plurality of goods supply and demand parameters of the target goods according to the goods operation information, the goods transportation parameters and preset goods transportation constraint conditions;
and determining the freight transportation mode of the target freight from the plurality of freight transportation modes according to the plurality of freight supply and demand parameters.
In some embodiments of the present application, the method further comprises:
acquiring detailed information of goods in the supply chain network;
wherein, the acquiring the freight transportation parameters of the target freight in the supply chain network comprises:
and determining the cargo transportation parameters of the target cargo according to the cargo detail information.
In some embodiments of the present application, the cargo detail information includes a total cargo amount and a single cargo size, the plurality of cargo transportation modes includes a logistics product transportation mode, and the cargo transportation parameters include cargo transportation parameters of the target cargo in the logistics product transportation mode; the plurality of cargo supply and demand parameters comprise cargo supply and demand parameters of the target cargo in a logistics product transportation mode;
the step of determining the cargo transportation parameters of the target cargo according to the cargo detail information comprises the following steps:
determining the parcel weight and the light throwing weight of the target cargo according to the cargo detail information, and taking the larger value of the parcel weight and the light throwing weight as the parcel actual weight of the target cargo;
determining the parcel continuous weight and the parcel overweight of the target cargo according to the parcel actual weight;
and determining the freight transportation parameters of the target freight in the logistics product transportation mode according to the real parcel weight, the continued parcel weight, the overweight parcel weight and a preset freight pricing strategy.
In some embodiments of the present application, the preset cargo pricing strategy includes a plurality of pricing strategies, each pricing strategy corresponding to a plurality of initial cargo transportation parameters;
the step of determining the freight transportation parameters of the target freight according to the real parcel weight, the continued parcel weight, the overweight parcel and a preset freight pricing strategy comprises the following steps:
acquiring the multiple pricing strategies to determine corresponding initial cargo transportation parameters;
determining corresponding initial freight transportation parameters according to the real parcel weight, the continued parcel weight, the overweight parcel weight and the multiple pricing strategies, and calculating multiple freight transportation parameters of the target freight under the multiple pricing strategies;
and taking the minimum value of the plurality of freight transportation parameters of the target freight under the plurality of pricing strategies as the freight transportation parameter of the target freight.
In some embodiments of the present application, the plurality of cargo transportation modes include a whole vehicle transportation mode, and the cargo transportation parameters include cargo transportation parameters of the target cargo in the whole vehicle transportation mode; the plurality of goods supply and demand parameters comprise goods supply and demand parameters under the whole vehicle transportation mode of the target goods;
the determining the cargo transportation parameters of the target cargo according to the cargo detail information comprises the following steps:
acquiring vehicle information for transporting the target cargo in the supply chain network, wherein the vehicle information comprises load information and capacity information of the vehicle transporting the target cargo;
and determining the cargo transportation parameters of the target cargo according to the vehicle information and the cargo detail information.
In some embodiments of the present application, the determining the cargo transportation parameter of the target cargo according to the vehicle information and the cargo detail information includes:
determining load transportation parameters of the vehicle for transporting the target cargo according to the load information of the vehicle and the cargo detail information;
determining a capacity transportation parameter of the vehicle for transporting the target cargo according to the capacity information of the vehicle and the cargo detail information;
and taking the smaller value of the load transportation cost and the capacity transportation cost as the cargo transportation parameter of the target cargo.
In some embodiments of the present application, the freight transportation parameters include a first freight transportation parameter from a factory to each warehouse of a target freight in the supply chain network, a second freight transportation parameter from each warehouse to each target freight customer, and a third freight transportation parameter between each warehouse, the first freight transportation parameter, the second freight transportation parameter, and the third freight transportation parameter.
In some embodiments of the present application, the determining, according to the cargo operation information, the cargo transportation parameter, and a preset cargo transportation constraint condition, a plurality of cargo supply and demand parameters of the target cargo includes:
and taking a preset cargo transportation constraint condition as a constraint, inputting the cargo operation information and the cargo transportation parameters into a preset cargo transportation objective function to plan the cargo transportation, and determining a plurality of cargo supply and demand parameters of the target cargo.
In another aspect, there is provided a cargo transportation mode determination apparatus, the apparatus including:
cargo transportation mode determining apparatus, characterized in that the apparatus comprises:
the first acquisition module is used for acquiring the goods operation information of the target goods in the current supply chain network;
the second acquisition module is used for acquiring the cargo transportation parameters of the target cargo in the supply chain network;
the first determining module is used for determining a plurality of goods supply and demand parameters of the target goods according to the goods operation information, the goods transportation parameters and preset goods transportation constraint conditions;
and the second determining module is used for determining the cargo transportation mode of the target cargo from the plurality of cargo transportation modes according to the plurality of cargo supply and demand parameters.
In some embodiments of the present application, the apparatus further comprises:
the third acquisition module is used for acquiring the detail information of the goods in the supply chain network;
the second obtaining module is specifically configured to: and determining the cargo transportation parameters of the target cargo according to the cargo detail information.
In some embodiments of the present application, the cargo detail information includes a total cargo amount and a single cargo size, the plurality of cargo transportation modes includes a logistics product transportation mode, and the cargo transportation parameters include cargo transportation parameters of the target cargo in the logistics product transportation mode; the plurality of cargo supply and demand parameters comprise cargo supply and demand parameters of the target cargo in a logistics product transportation mode;
the second obtaining module is specifically configured to:
determining the parcel weight and the light throwing weight of the target cargo according to the cargo detail information, and taking the larger value of the parcel weight and the light throwing weight as the parcel actual weight of the target cargo;
determining the parcel continuous weight and the parcel overweight of the target cargo according to the parcel actual weight;
and determining the freight transportation parameters of the target freight in the logistics product transportation mode according to the real parcel weight, the continued parcel weight, the overweight parcel weight and a preset freight pricing strategy.
In some embodiments of the present application, the preset cargo pricing strategy includes a plurality of pricing strategies, each pricing strategy corresponding to a plurality of initial cargo transportation parameters;
the second obtaining module is specifically configured to:
acquiring the multiple pricing strategies to determine corresponding initial cargo transportation parameters;
determining corresponding initial freight transportation parameters according to the real parcel weight, the continued parcel weight, the overweight parcel and the multiple pricing strategies, and calculating multiple freight transportation parameters of the target freight under the multiple pricing strategies;
and taking the minimum value of the plurality of freight transportation parameters of the target freight under the plurality of pricing strategies as the freight transportation parameter of the target freight.
In some embodiments of the present application, the plurality of cargo transportation modes include a whole vehicle transportation mode, and the cargo transportation parameters include cargo transportation parameters of the target cargo in the whole vehicle transportation mode; the plurality of cargo supply and demand parameters comprise cargo supply and demand parameters under the whole vehicle transportation mode of the target cargo;
the second obtaining module is specifically configured to: acquiring vehicle information for transporting the target cargo in the supply chain network, wherein the vehicle information comprises load information and capacity information of the vehicle transporting the target cargo; and determining the cargo transportation parameters of the target cargo according to the vehicle information and the cargo detail information.
In some embodiments of the present application, the second obtaining module is specifically configured to:
determining load transportation parameters of the vehicle for transporting the target cargo according to the load information of the vehicle and the cargo detail information;
determining a capacity transportation parameter of the vehicle for transporting the target cargo according to the capacity information of the vehicle and the cargo detail information;
and taking the smaller value of the load transportation cost and the capacity transportation cost as the cargo transportation parameter of the target cargo.
In some embodiments of the present application, the freight transportation parameters include a first freight transportation parameter from a factory to each warehouse of a target freight in the supply chain network, a second freight transportation parameter from each warehouse to each target freight customer, and a third freight transportation parameter between each warehouse, the first freight transportation parameter, the second freight transportation parameter, and the third freight transportation parameter.
In some embodiments of the present application, the first determining module is specifically configured to:
and taking a preset cargo transportation constraint condition as a constraint, inputting the cargo operation information and the cargo transportation parameters into a preset cargo transportation objective function to plan the cargo transportation, and determining a plurality of cargo supply and demand parameters of the target cargo.
According to an aspect of the present application, there is also provided a computer apparatus, the apparatus comprising:
one or more processors;
a memory; and
one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to perform the operations of any of the methods described above.
According to an aspect of the application, there is also provided a computer-readable storage medium having stored thereon a computer program, which is loaded by a processor to perform the operations of any of the methods described above.
In the method, the goods operation information of the target goods in the current supply chain network is acquired; acquiring goods transportation parameters of target goods in the supply chain network; determining a plurality of goods supply and demand parameters of the target goods according to the goods operation information, the goods transportation parameters and preset goods transportation constraint conditions; and determining the cargo transportation mode of the target cargo from a plurality of cargo transportation modes according to the plurality of cargo supply and demand parameters. The method and the device are based on production and marketing balance, can be suitable for supply chain optimization under various scenes, combine the relation between supply and demand and the relation between transportation modes, determine the most appropriate target cargo transportation mode, optimize the cost of the supply chain and improve the efficiency of cargo transportation.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart illustrating an embodiment of a cargo transportation mode determining method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart diagram illustrating one embodiment of determining a cargo transportation parameter of a target cargo provided by an embodiment of the present application;
fig. 3 shows functional modules of the cargo transportation mode determination device provided in the embodiment of the present application;
FIG. 4 illustrates an exemplary system that can be used to implement the various embodiments described in this application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention. Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In this application, the word "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for the purpose of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes are not shown in detail to avoid obscuring the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
It should be noted that, since the method in the embodiment of the present application is executed in a computer device, processing objects of each computing device exist in the form of data or information, for example, time, which is substantially time information, it is understood that, in the subsequent embodiments, if size, number, position, and the like are mentioned, corresponding data exist, so that the computer device performs processing, and details are not described herein.
In a typical configuration of the present application, a terminal or a trusted party, etc. includes one or more processors, such as a Central Processing Unit (CPU), an input/output interface, a network interface, and a memory. The Memory may include forms of volatile Memory, random Access Memory (RAM), and/or non-volatile Memory in a computer-readable medium, such as Read Only Memory (ROM) or Flash Memory. Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase-Change Memory (PCM), programmable Random Access Memory (PRAM), static Random-Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash Memory or other Memory technology, compact Disc Read Only Memory (CD-ROM), digital Versatile Disc (DVD) or other optical storage, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
The device referred to in this application includes, but is not limited to, a user device, a network device, or a device formed by integrating a user device and a network device through a network. The user equipment includes, but is not limited to, any mobile electronic product, such as a smart phone, a tablet computer, etc., capable of performing human-computer interaction with a user (e.g., human-computer interaction through a touch panel), and the mobile electronic product may employ any operating system, such as an Android operating system, an iOS operating system, etc. The network Device includes an electronic Device capable of automatically performing numerical calculation and information processing according to a preset or stored instruction, and the hardware includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded Device, and the like. The network device includes but is not limited to a computer, a network host, a single network server, a plurality of network server sets or a cloud of a plurality of servers; here, the Cloud is composed of a large number of computers or network servers based on Cloud Computing (Cloud Computing), which is a kind of distributed Computing, one virtual supercomputer consisting of a collection of loosely coupled computers. Including, but not limited to, the internet, a wide area network, a metropolitan area network, a local area network, a VPN network, a wireless Ad Hoc network (Ad Hoc network), etc. Preferably, the device may also be a program running on the user device, the network device, or a device formed by integrating the user device and the network device, the touch terminal, or the network device and the touch terminal through a network.
Of course, those skilled in the art will appreciate that the foregoing is by way of example only, and that other existing or future devices, which may be suitable for use in the present application, are also encompassed within the scope of the present application and are hereby incorporated by reference.
FIG. 1 illustrates a freight mode determination method, which may be applied to a computer device, according to one aspect of the present application. In this embodiment, the computer device may be an independent server, or may be a server network or a server cluster composed of servers, for example, the computer device described in this embodiment includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud server composed of a plurality of servers. Among them, the Cloud server is constituted by a large number of computers or web servers based on Cloud Computing (Cloud Computing). The method comprises the following steps 101-104:
101. and acquiring the goods operation information of the target goods in the current supply chain network.
The supply chain network refers to a network chain structure formed by upstream and downstream enterprises which provide products or services to end user activities in the production and circulation process. The supply chain network mainly comprises three parties, namely a factory corresponding to the factory, a distribution center corresponding to the warehouse, an addressee site corresponding to the customer and the like, wherein the number of each party can be set to be multiple according to the requirement of the supply chain.
102. And acquiring the freight transportation parameters of the target goods in the supply chain network.
103. And determining a plurality of goods supply and demand parameters of the target goods according to the goods operation information, the goods transportation parameters and preset goods transportation constraint conditions.
104. And determining the freight transportation mode of the target freight from the plurality of freight transportation modes according to the plurality of freight supply and demand parameters.
In the method, the goods operation information of the target goods in the current supply chain network is acquired; acquiring goods transportation parameters of target goods in the supply chain network; determining a plurality of goods supply and demand parameters of the target goods according to the goods operation information, the goods transportation parameters and preset goods transportation constraint conditions; and determining the cargo transportation mode of the target cargo from a plurality of cargo transportation modes according to the plurality of cargo supply and demand parameters. The method and the device are based on production and marketing balance, can be suitable for supply chain optimization under various scenes, combine the relation between supply and demand and the relation between transportation modes, determine the most appropriate target cargo transportation mode, optimize the cost of the supply chain and improve the efficiency of cargo transportation.
The goods operation information of the target goods in the current supply chain network can be operation income information of the target goods in the supply chain network, and specifically, the operation income information is determined by customer demand information, customer shortage cost information, factory production cost information and warehouse goods holding cost information.
Specifically, for example, the computer device obtains operation profit information on the supply chain network, where the operation profit information includes customer demand information, customer backorder cost information, factory production cost information, warehouse Stock cost information, and the like, where the customer demand information includes profits brought by actual demands of customers, generally determined by supply volumes of warehouses to customers and demand profits from Unit inventory lists, such as supply volumes of various warehouses multiplied by Stock Keeping Units (SKU) demand profits, and the like. The customer shortage cost information includes loss due to shortage of the customer goods, and the like, and mainly includes profit loss caused when the supply quantity is smaller than the customer demand quantity. The plant production costs include the production costs of the plant to warehouse delivery of goods, as determined by the amount of goods delivered by the plant to warehouse and the plant SKU production costs. The warehouse holding cost information includes a loss consumed when the goods passed through the warehouse are stored in the warehouse, such as a loss caused by storing the goods.
Specifically, the corresponding operation income information calculation method is as follows:
in the formula (1), the first half part in the first item is customer demand information, and the second half part is customer shortage cost information; the total first statistic is the income brought by operation, the second is corresponding factory production cost information, and the third is warehouse goods cost information and the like.
Wherein, the meaning of each parameter is as follows:
m belongs to M and is a factory index and set; w belongs to W and is the warehouse index and set; c belongs to C and is the index and the set of the client; s belongs to S and comprises sku index and set; f belongs to F, goods supply path index and set, F i Representing a set of pre-paths, F j Representing post path joining; d cs Customer sku demand; y is ms Total yield of sku in factory; r is cs Client sku demand income; bc is cs Customer sku out-of-stock cost; pc (personal computer) ms Factory sku production cost; h is ws Warehouse stocking cost (operation cost); tc fs (q) transportation cost when the transportation amount is q; q. q.s ijs Mesh point i supplies the total amount of sku to mesh point j, continuously deciding on the variables.
Further, the method further comprises: acquiring detail information of the goods in the supply chain network, wherein the acquiring of the freight transportation parameters of the target goods in the supply chain network comprises: and determining the cargo transportation parameters of the target cargo according to the cargo detail information.
In an embodiment of the present application, the freight transportation parameters include a first freight transportation parameter from a factory of a target freight to each warehouse in the supply chain network, a second freight transportation parameter from each warehouse to each target freight customer, and a third freight transportation parameter between each warehouse, and the first freight transportation parameter, the second freight transportation parameter, and the third freight transportation parameter. Specifically, the freight transportation parameter may be freight transportation cost information, wherein the freight transportation cost information includes factory-to-warehouse freight transportation cost information, warehouse-to-customer freight transportation cost information, and warehouse-to-warehouse freight transportation cost information.
For example, in addition to the above calculated costs, the goods may also cause a certain transportation cost loss during transportation, and the transportation cost information of the goods exists during transportation from a factory to a warehouse, delivery between warehouses, and delivery from the warehouse to a client. The specific calculation method is as follows:
in the formula (2), the first item is the freight cost information of the industrial warehouse freight transported from each factory to each warehouse, the second item is the freight cost information of the passenger freight transported from each warehouse to each customer, and the third item is the freight cost information of the warehouse freight caused by the delivery of the freight between each warehouse. The warehouse comprises a central distribution center and a regional distribution center, and the freight transportation cost information of the warehouses mainly comprises the transportation cost and the like caused by the fact that the cargos are distributed to the regional distribution center from the central distribution center.
In the embodiment of the application, the cargo transportation mode includes but is not limited to one or more of a logistics product transportation mode and a vehicle transportation mode. And aiming at different scenes, the transportation mode corresponding to the goods can be determined, and the transportation cost information of the corresponding goods is calculated according to the transportation constraint conditions of the transportation mode. If the detailed information of the goods is obtained firstly, the detailed information of the goods comprises the total weight of the goods, the size of a single piece of goods and the like, and the transportation mode of the goods is determined according to the weight, the volume and the like of the goods; specifically, small, light in weight's goods can adopt commodity circulation product mode express mail etc. to transport, and bulky, heavy in weight's goods can adopt the mode of car dress to carry out whole car transportation etc. and different transportation modes have different restraint conditions.
For example, the cargo transportation mode includes a logistics product transportation mode and a vehicle transportation mode, wherein for various types of cargos in the same batch, different transportation mode ratios and the like can be adopted according to the supply amount of various types of cargos, and for example, various forms such as a logistics product transportation mode which is adopted completely, a vehicle transportation mode which is adopted completely, or a part of logistics product transportation mode and a part of vehicle transportation mode are combined, and the like, and here, specific configuration is not limited, and the like.
When the plurality of cargo transportation modes comprise a logistics product transportation mode, the cargo detail information comprises the total amount of the cargo and the size of the single piece of cargo, and the cargo transportation parameters comprise the cargo transportation parameters of the target cargo in the logistics product transportation mode; the plurality of cargo supply and demand parameters comprise cargo supply and demand parameters of the target cargo in a logistics product transportation mode.
At this time, as shown in fig. 2, the determining the cargo transportation parameter of the target cargo according to the cargo detail information further includes the following steps 201 to 203:
201. determining the parcel weight and the light throwing weight of the target cargo according to the cargo detail information, and taking the larger value of the parcel weight and the light throwing weight as the parcel actual weight of the target cargo.
202. And determining the parcel continuous weight and the parcel overweight of the target cargo according to the parcel actual weight.
203. And determining the freight transportation parameters of the target freight in the logistics product transportation mode according to the real parcel weight, the continued parcel weight, the overweight parcel weight and a preset freight pricing strategy.
Further, the preset goods pricing strategy comprises a plurality of pricing strategies, and each pricing strategy corresponds to a plurality of initial goods transportation parameters.
The determining the freight transportation parameters of the target freight according to the real parcel weight, the continued parcel weight, the overweight parcel weight and a preset freight pricing strategy comprises the following steps: acquiring the multiple pricing strategies to determine corresponding initial cargo transportation parameters; determining corresponding initial freight transportation parameters according to the real parcel weight, the continued parcel weight, the overweight parcel weight and the multiple pricing strategies, and calculating multiple freight transportation parameters of the target freight under the multiple pricing strategies; and taking the minimum value of the plurality of freight transportation parameters of the target freight under the plurality of pricing strategies as the freight transportation parameter of the target freight.
Taking the freight transportation parameters as freight transportation cost information as an example, determining corresponding freight transportation cost information according to the real parcel weight, the continued parcel weight, the overweight parcel weight and a preset freight pricing strategy.
For example, when the logistics product transportation mode is adopted, the goods need to be packaged, and information related to the package, such as the real weight of the package, the continuous weight of the package, the overweight of the package, and the like, is determined. The specific calculation is as follows:
the parameters are defined as follows: z represents weight, l represents current pricing strategy, α l For preset parameter values, bw l ,bp l ,up l ,mw l ,lf l Respectively representing the first weight, the first weight price, the subsequent weight price, the maximum weight, the light throwing coefficient and the like of the corresponding packages of the logistics products; omega s Sku weight; upsilon is s Sku volume; l belongs to L, indexing and collecting logistics transportation mode, L o And the logistics transportation mode set represents the corresponding flow direction of the order.
The transportation constraint conditions of the specific logistics product transportation are as follows:
1) Actual weight of package z p Is weight (kg) and light weight of throwing omega p (volume v) p Coefficient of light polishing lf l ) The larger of these values:
z p ≥ω p ,z p ≥υ p /lf l (5)
wherein z is p ≥0；
2) Wrapping continued weight zbw p And wrapping overweight zmw p Value calculation
zbw p ≥z p -bw l ,zbw p ≥0 (6)
zmw p ≥z p -mw l ，zmw p ≥0 (7)
Then, the freight transportation cost information of the package p under the current pricing strategy l is:
for the foregoing calculation process, a real weight determination of the parcel may also be performed, for example, whether the real weight of the parcel is equal to 0 is determined as follows:
in some embodiments, the current pricing strategy includes a plurality of pricing strategies, and determining corresponding freight transportation cost information according to the real weight of the package, the continued weight of the package, the overweight weight of the package, and a preset freight pricing strategy includes: acquiring the multiple pricing strategies to determine corresponding initial cargo transportation parameters; determining corresponding initial freight transportation cost according to the real parcel weight, the continued parcel weight, the overweight parcel weight and the multiple pricing strategies, and calculating multiple freight transportation costs of the target freight under the multiple pricing strategies; and taking the minimum value of the multiple freight transportation costs of the target freight under the multiple pricing strategies as the freight transportation cost of the target freight.
For example, different pricing strategies exist for the transportation of packaged logistics products according to different weights or volumes, and the minimum value of the transportation cost of goods under all the transportation strategies of goods is usually taken as follows:
wherein, the formula (10) satisfies the following condition:
in other embodiments of the present application, when the plurality of cargo transportation modes includes a whole vehicle transportation mode, the cargo transportation parameter includes a cargo transportation parameter of the target cargo in the whole vehicle transportation mode; the plurality of goods supply and demand parameters comprise goods supply and demand parameters under the whole vehicle transportation mode of the target goods.
At this time, the determining the cargo transportation parameter of the target cargo according to the cargo detail information may include: acquiring vehicle information for transporting the target cargo in the supply chain network, wherein the vehicle information comprises load information and capacity information of the vehicle transporting the target cargo; and determining the cargo transportation parameters of the target cargo according to the vehicle information and the cargo detail information.
Further, the determining the cargo transportation parameter of the target cargo according to the vehicle information and the cargo detail information includes: determining load transportation parameters of the vehicle for transporting the target cargo according to the load information of the vehicle and the cargo detail information; determining a capacity transportation parameter of the vehicle for transporting the target cargo according to the capacity information of the vehicle and the cargo detail information; and taking the smaller value of the load transportation cost and the capacity transportation cost as the cargo transportation parameter of the target cargo.
In a specific embodiment, if the entire vehicle transportation mode is adopted, the number of cargos which can be accommodated by each vehicle for cargo transportation needs to be calculated, the required vehicles are further calculated, and the corresponding cargo transportation cost information is determined according to the unit price of each vehicle. The specific vehicle transportation mode comprises a weight pricing mode and a capacity pricing mode, for example, load information or capacity information of corresponding vehicles is obtained, the required number of the vehicles is calculated according to the load information or the capacity information, and corresponding cargo transportation cost information is determined according to the unit price information of the vehicles. In some embodiments, the determining the corresponding cargo transportation cost information according to the vehicle information and the cargo detail information includes: determining corresponding load cargo transportation cost information according to the load information of the vehicle and the cargo detail information; determining the transportation cost information of the corresponding volume goods according to the volume information of the vehicle and the detail information of the goods; and comparing the load cargo transportation cost information with the capacity cargo transportation cost information, and taking a smaller value as corresponding cargo transportation cost information.
The specific calculation method is as follows:
v belongs to V, namely the set of vehicle types of the whole vehicle, V wc Representing a set of factory-to-customer available vehicle types; omega v ,υ v ,p v Maximum weight and volume of vehicle type, price of bicycle; n is a radical of an alkyl radical wcv The number of the fixed vehicle types selected from the warehouse to the client; then if the total vehicle load from warehouse m to customer c can cover the demand:
if the total vehicle volume of warehouse m to customer c can cover the demand:
the corresponding load cargo transportation cost information and the corresponding capacity cargo transportation cost information can be calculated according to the formula (12) and the formula (13), the sizes of the load cargo transportation cost information and the capacity cargo transportation cost information are compared, and the smaller value is taken as the corresponding cargo transportation cost information.
Further, the determining a plurality of cargo supply and demand parameters of the target cargo according to the cargo operation information, the cargo transportation parameters and preset cargo transportation constraint conditions includes: and taking a preset cargo transportation constraint condition as a constraint, inputting the cargo operation information and the cargo transportation parameters into a preset cargo transportation objective function to plan the cargo transportation, and determining a plurality of cargo supply and demand parameters of the target cargo.
For example, after determining the operation income information and the freight transportation cost information, the computer device establishes a corresponding calculation model according to the freight transportation constraint condition, calculates the supply and demand cost information on the supply chain according to the calculation model, and the like. For example, a greedy algorithm is used, modeling is performed by using a linear programming tool, a solving tool and the like, corresponding scene information is input, an output optimal result is obtained, and the optimal result is used as corresponding supply and demand cost information and the like. The known input scenario information includes, for example, the known conditions, including but not limited to a factory address, a warehouse address, a customer address, unit transportation fees in each process, unit period fixed operation costs, supply amount in each process, and the like, and further includes preset constraints. Generally, the optimal result is to minimize the transportation cost while maximizing the operation cost under the constraint condition, in other words, each supply and demand cost information is different according to the difference of the corresponding cargo transportation modes, for example, the optimal solution can be determined by maximizing the difference between the operation cost information and the cargo transportation cost information.
Specifically, the multiple goods supply and demand parameters are multiple supply and demand costs, for example, and the corresponding target goods transportation mode is determined from the multiple goods transportation modes according to the multiple supply and demand costs. For example, according to a plurality of supply and demand cost information, a freight transportation mode required by a user can be selected from the supply and demand cost information, such as determining the freight transportation mode with the largest supply and demand cost as a corresponding target transportation mode. Furthermore, according to different types of goods on the supply chain, the respective corresponding goods transportation modes of different types of goods can be determined.
In some embodiments, the preset cargo transportation constraints include, but are not limited to: the customer demand of the customer is less than the total demand of the warehouse; the input quantity of the warehouse is larger than the output quantity of the warehouse; the shipment volume of the plant is less than the total production volume of the plant.
For example, as for the cargo transportation constraint conditions, one or more of the constraint conditions can be selected as follows:
1) The customer demand of the customer is less than the total demand of the warehouse, i.e. the customer demand capacity is less than the total demand:
wherein, the formula (2) satisfies 0 ≦ sd cs ≤d cs ,
S belongs to S and the like;
2) The warehouse has the following advantages that the warehouse has the goods input amount larger than the goods output amount of the warehouse, namely the warehouse has the goods input amount larger than the goods output amount:
3) The factory shipment is less than the total production of the factory, i.e. the factory shipment is less than the total production:
embodiments of a cargo transportation mode determining method according to an aspect of the present application are mainly described above, and an apparatus capable of implementing the embodiments is provided, and is described below with reference to fig. 2.
Fig. 3 illustrates a cargo transportation mode determination device according to an aspect of the present application, the device 300 comprising:
a first obtaining module 301, configured to obtain goods operation information of a target good in a current supply chain network;
a second obtaining module 302, configured to obtain a cargo transportation parameter of a target cargo in the supply chain network;
a first determining module 303, configured to determine, according to the cargo operation information, the cargo transportation parameters, and preset cargo transportation constraint conditions, a plurality of cargo supply and demand parameters of the target cargo;
a second determining module 304, configured to determine a cargo transportation mode of the target cargo from the plurality of cargo transportation modes according to the plurality of cargo supply and demand parameters.
In the application, the first obtaining module 301 obtains the cargo operation information of the target cargo in the current supply chain network; the second obtaining module 302 is configured to obtain a cargo transportation parameter of a target cargo in the supply chain network; the first determining module 303 determines a plurality of cargo supply and demand parameters of the target cargo according to the cargo operation information, the cargo transportation parameters and the preset cargo transportation constraint conditions; the second determining module 304 determines a cargo transportation mode of the target cargo from a plurality of cargo transportation modes according to the plurality of cargo supply and demand parameters. The embodiment of the application is based on production and marketing balance, can be suitable for supply chain optimization under various scenes, combines the relation between supply and demand and the relation between transportation modes, determines the most appropriate target cargo transportation mode, optimizes the cost of the supply chain and improves the cargo transportation efficiency.
In some embodiments of the present application, the apparatus further comprises:
the third acquisition module is used for acquiring the detail information of the goods in the supply chain network;
the second obtaining module is specifically configured to: and determining the cargo transportation parameters of the target cargo according to the cargo detail information.
In some embodiments of the present application, the cargo detail information includes a total cargo amount and a single cargo size, the plurality of cargo transportation modes includes a logistics product transportation mode, and the cargo transportation parameters include cargo transportation parameters of the target cargo in the logistics product transportation mode; the plurality of cargo supply and demand parameters comprise cargo supply and demand parameters of the target cargo in a logistics product transportation mode;
the second obtaining module is specifically configured to:
determining the parcel weight and the light throwing weight of the target cargo according to the cargo detail information, and taking the larger value of the parcel weight and the light throwing weight as the parcel actual weight of the target cargo;
determining the parcel continuous weight and the parcel overweight of the target goods according to the parcel actual weight;
and determining the freight transportation parameters of the target freight in the logistics product transportation mode according to the real parcel weight, the continued parcel weight, the overweight parcel weight and a preset freight pricing strategy.
In some embodiments of the present application, the preset cargo pricing strategy includes a plurality of pricing strategies, each pricing strategy corresponding to a plurality of initial cargo transportation parameters;
the second obtaining module is specifically configured to:
acquiring the multiple pricing strategies to determine corresponding initial cargo transportation parameters;
determining corresponding initial freight transportation parameters according to the real parcel weight, the continued parcel weight, the overweight parcel weight and the multiple pricing strategies, and calculating multiple freight transportation parameters of the target freight under the multiple pricing strategies;
and taking the minimum value of the plurality of freight transportation parameters of the target freight under the plurality of pricing strategies as the freight transportation parameter of the target freight.
In some embodiments of the present application, the plurality of cargo transportation modes includes a whole vehicle transportation mode, and the cargo transportation parameter includes a cargo transportation parameter of the target cargo in the whole vehicle transportation mode; the plurality of cargo supply and demand parameters comprise cargo supply and demand parameters under the whole vehicle transportation mode of the target cargo;
the second obtaining module is specifically configured to: acquiring vehicle information for transporting the target cargo in the supply chain network, wherein the vehicle information comprises load information and capacity information of the vehicle transporting the target cargo; and determining the cargo transportation parameters of the target cargo according to the vehicle information and the cargo detail information.
In some embodiments of the present application, the second obtaining module is specifically configured to:
determining load transportation parameters of the vehicle for transporting the target cargo according to the load information of the vehicle and the cargo detail information;
determining a capacity transportation parameter of the vehicle for transporting the target cargo according to the capacity information of the vehicle and the cargo detail information;
and taking the smaller value of the load transportation cost and the capacity transportation cost as the cargo transportation parameter of the target cargo.
In some embodiments of the present application, the freight transportation parameters include a first freight transportation parameter from a factory to each warehouse of a target freight in the supply chain network, a second freight transportation parameter from each warehouse to each target freight customer, and a third freight transportation parameter between each warehouse, the first freight transportation parameter, the second freight transportation parameter, and the third freight transportation parameter.
In some embodiments of the present application, the first determining module is specifically configured to:
and taking a preset cargo transportation constraint condition as a constraint, inputting the cargo operation information and the cargo transportation parameters into a preset cargo transportation objective function to plan the cargo transportation, and determining a plurality of cargo supply and demand parameters of the target cargo.
In addition to the methods and apparatus described in the embodiments above, the present application also provides a computer-readable storage medium storing computer code that, when executed, performs the method described in any of the preceding claims.
The present application also provides a computer program product, which when executed by a computer device performs the method of any of the preceding claims.
The present application further provides a computer device, comprising:
one or more processors;
a memory for storing one or more computer programs;
the one or more computer programs, when executed by the one or more processors, cause the one or more processors to implement the method of any preceding claim.
FIG. 4 illustrates an exemplary system that can be used to implement the various embodiments described herein;
in some embodiments, as illustrated in FIG. 4, the system 400 can be implemented as any of the devices described in the various embodiments. In some embodiments, system 400 may include one or more computer-readable media (e.g., system Memory or non-volatile Memory (non-volatile Memory) NVM/storage 420) having instructions and one or more processors (e.g., processor(s) 405) coupled with the one or more computer-readable media and configured to execute the instructions to implement modules to perform the actions described herein.
For one embodiment, system control module 410 may include any suitable interface controllers to provide any suitable interface to at least one of the processor(s) 405 and/or any suitable device or component in communication with system control module 410.
The system control module 410 may include a memory controller module 430 to provide an interface to the system memory 415. The memory controller module 430 may be a hardware module, a software module, and/or a firmware module.
For one embodiment, system control module 410 may include one or more input/output (I/O) controllers to provide an interface to NVM/storage 420 and communication interface(s) 425.
For example, NVM/storage 420 may be used to store data and/or instructions. NVM/storage 420 may include any suitable non-volatile memory (e.g., flash memory) and/or may include any suitable non-volatile storage device(s) (e.g., one or more Hard Disk Drive(s) (HDD (s)), one or more Compact Disc (CD) Drive(s), and/or one or more Digital Versatile Disc (DVD) Drive (s)).
NVM/storage 420 may include storage resources that are physically part of the device on which system 400 is installed or may be accessed by the device and not necessarily part of the device. For example, NVM/storage 420 may be accessed over a network via communication interface(s) 425.
Communication interface(s) 425 may provide an interface for system 400 to communicate over one or more networks and/or with any other suitable device. System 400 may wirelessly communicate with one or more components of a wireless network according to any of one or more wireless network standards and/or protocols.
For one embodiment, at least one of the processor(s) 405 may be packaged together with logic for one or more controller(s) of the system control module 410, such as memory controller module 430. For one embodiment, at least one of the processor(s) 405 may be packaged together with logic for one or more controller(s) of the System control module 410 to form a System in a Package (SiP). For one embodiment, at least one of the processor(s) 405 may be integrated on the same die with logic for one or more controller(s) of the system control module 410. For one embodiment, at least one of the processor(s) 405 may be integrated on the same die with logic for one or more controller(s) of the System control module 410 to form a System on Chip (SoC).
In various embodiments, system 400 may be, but is not limited to being: a server, a workstation, a desktop computing device, or a mobile computing device (e.g., a laptop computing device, a handheld computing device, a tablet, a netbook, etc.). In various embodiments, system 400 may have more or fewer components and/or different architectures. For example, in some embodiments, system 400 includes one or more cameras, a keyboard, a Liquid Crystal Display (LCD) screen (including a touch screen Display), a non-volatile memory port, a plurality of antennas, a graphics chip, an Application Specific Integrated Circuit (ASIC), and a speaker.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, some of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application through the operation of the computer. Those skilled in the art will appreciate that the form in which the computer program instructions reside on a computer-readable medium includes, but is not limited to, source files, executable files, installation package files, and the like, and that the manner in which the computer program instructions are executed by a computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Computer-readable media herein can be any available computer-readable storage media or communication media that can be accessed by a computer.
Communication media includes media by which communication signals, including, for example, computer readable instructions, data structures, program modules, or other data, are transmitted from one system to another. Communication media may include conductive transmission media such as cables and wires (e.g., fiber optics, coaxial, etc.) and wireless (non-conductive transmission) media capable of propagating energy waves such as acoustic, electromagnetic, RF, microwave, and infrared. Computer readable instructions, data structures, program modules or other data may be embodied in a modulated data signal, such as a carrier wave or similar mechanism that is embodied in a wireless medium, such as part of spread-spectrum techniques, for example. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. The modulation may be analog, digital, or hybrid modulation techniques.
By way of example, and not limitation, computer-readable storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. For example, computer-readable storage media include, but are not limited to, volatile memory such as random access memory (RAM, DRAM, SRAM); and nonvolatile memories such as flash memories, various read only memories (ROM, PROM, EPROM, EEPROM), magnetic and ferromagnetic (MRAM)/Ferroelectric memories ferro electric RAM, feRAM); and magnetic and optical storage devices (hard disk, tape, CD, DVD); or other now known media or later developed that can store computer-readable information/data for use by a computer system.
An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to the aforementioned embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware.
The cargo transportation mode determining method, apparatus, computer device and storage medium provided in the embodiments of the present application are described in detail above, and specific examples are applied herein to explain the principles and embodiments of the present invention, and the description of the embodiments is only used to help understand the method and its core ideas of the present invention; meanwhile, for those skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed, and in summary, the content of the present specification should not be construed as limiting the present invention.
Claims (11)
1. A cargo transportation mode determination method, characterized in that the method comprises:
acquiring goods operation information of target goods in a current supply chain network;
acquiring goods transportation parameters of target goods in the supply chain network;
determining a plurality of goods supply and demand parameters of the target goods according to the goods operation information, the goods transportation parameters and preset goods transportation constraint conditions;
and determining the freight transportation mode of the target freight from the plurality of freight transportation modes according to the plurality of freight supply and demand parameters.
2. The cargo transportation mode determination method of claim 1, further comprising:
acquiring detailed information of goods in the supply chain network;
wherein the acquiring of the freight transportation parameters of the target freight in the supply chain network includes:
and determining the cargo transportation parameters of the target cargo according to the cargo detail information.
3. The cargo transportation mode determination method according to claim 2, wherein the cargo detail information includes a total amount of cargo and a size of a piece of cargo, the plurality of cargo transportation modes include a logistics product transportation mode, and the cargo transportation parameter includes a cargo transportation parameter of the target cargo in the logistics product transportation mode; the plurality of cargo supply and demand parameters comprise cargo supply and demand parameters of the target cargo in a logistics product transportation mode;
the determining the cargo transportation parameters of the target cargo according to the cargo detail information comprises the following steps:
determining the parcel weight and the light throwing weight of the target cargo according to the cargo detail information, and taking the larger value of the parcel weight and the light throwing weight as the parcel actual weight of the target cargo;
determining the parcel continuous weight and the parcel overweight of the target cargo according to the parcel actual weight;
and determining the freight transportation parameters of the target freight in the logistics product transportation mode according to the real parcel weight, the continued parcel weight, the overweight parcel weight and a preset freight pricing strategy.
4. The freight transportation mode determination method according to claim 3, wherein the preset freight pricing strategy includes a plurality of pricing strategies, each pricing strategy corresponding to a plurality of initial freight transportation parameters;
the determining the freight transportation parameters of the target freight according to the real parcel weight, the continued parcel weight, the overweight parcel weight and a preset freight pricing strategy comprises the following steps:
acquiring the multiple pricing strategies to determine corresponding initial cargo transportation parameters;
determining corresponding initial freight transportation parameters according to the real parcel weight, the continued parcel weight, the overweight parcel weight and the multiple pricing strategies, and calculating multiple freight transportation parameters of the target freight under the multiple pricing strategies;
and taking the minimum value of the freight transportation parameters of the target freight under the multiple pricing strategies as the freight transportation parameter of the target freight.
5. The freight transportation mode determination method according to claim 2, wherein the plurality of freight transportation modes include a vehicle transportation mode, and the freight transportation parameter includes a freight transportation parameter of the target freight in the vehicle transportation mode; the plurality of cargo supply and demand parameters comprise cargo supply and demand parameters under the whole vehicle transportation mode of the target cargo;
the step of determining the cargo transportation parameters of the target cargo according to the cargo detail information comprises the following steps:
acquiring vehicle information for transporting the target cargo in the supply chain network, wherein the vehicle information comprises load information and capacity information of the vehicle transporting the target cargo;
and determining the cargo transportation parameters of the target cargo according to the vehicle information and the cargo detail information.
6. The method of claim 5, wherein determining the cargo transportation parameter of the target cargo according to the vehicle information and the cargo detail information comprises:
determining load transportation parameters of the vehicle for transporting the target cargo according to the load information of the vehicle and the cargo detail information;
determining a capacity transportation parameter of the vehicle for transporting the target cargo according to the capacity information of the vehicle and the cargo detail information;
and taking the smaller value of the load transportation cost and the capacity transportation cost as the cargo transportation parameter of the target cargo.
7. The freight transportation mode determination method according to any one of claims 1 to 6, wherein the freight transportation parameters include a factory-to-warehouse first freight transportation parameter of a target freight in the supply chain network, a warehouse-to-warehouse second freight transportation parameter of a target freight customer, and a warehouse-to-warehouse third freight transportation parameter, the first freight transportation parameter, the second freight transportation parameter, and the third freight transportation parameter.
8. The cargo transportation mode determining method according to any one of claims 1 to 6, wherein the determining a plurality of cargo supply and demand parameters of the target cargo according to the cargo operation information, the cargo transportation parameters and preset cargo transportation constraint conditions includes:
and taking a preset cargo transportation constraint condition as a constraint, inputting the cargo operation information and the cargo transportation parameters into a preset cargo transportation objective function to plan the cargo transportation, and determining a plurality of cargo supply and demand parameters of the target cargo.
9. A cargo transportation mode determining apparatus, characterized in that the apparatus comprises:
the first acquisition module is used for acquiring the goods operation information of the target goods in the current supply chain network;
the second acquisition module is used for acquiring the cargo transportation parameters of the target cargo in the supply chain network;
the first determining module is used for determining a plurality of goods supply and demand parameters of the target goods according to the goods operation information, the goods transportation parameters and preset goods transportation constraint conditions;
and the second determining module is used for determining the cargo transportation mode of the target cargo from the plurality of cargo transportation modes according to the plurality of cargo supply and demand parameters.
10. A computer device, the device comprising:
one or more processors;
a memory; and
one or more application programs, wherein the one or more application programs are stored in the memory and configured to perform the operations of the method of any of claims 1-8 by the processor.
11. A computer-readable storage medium, having stored thereon a computer program which is loaded by a processor to perform operations of the method according to any of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110857347.8A CN115700672A (en) | 2021-07-28 | 2021-07-28 | Cargo transportation mode determining method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110857347.8A CN115700672A (en) | 2021-07-28 | 2021-07-28 | Cargo transportation mode determining method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115700672A true CN115700672A (en) | 2023-02-07 |
Family
ID=85120576
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110857347.8A Pending CN115700672A (en) | 2021-07-28 | 2021-07-28 | Cargo transportation mode determining method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115700672A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116468342A (en) * | 2023-04-06 | 2023-07-21 | 宝驷智慧物流(珠海)有限公司 | Logistics transportation management method, system, device, storage medium and electronic equipment |
-
2021
- 2021-07-28 CN CN202110857347.8A patent/CN115700672A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116468342A (en) * | 2023-04-06 | 2023-07-21 | 宝驷智慧物流(珠海)有限公司 | Logistics transportation management method, system, device, storage medium and electronic equipment |
| CN116468342B (en) * | 2023-04-06 | 2024-03-12 | 宝驷智慧物流(珠海)有限公司 | Logistics transportation management method, system, device, storage medium and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109426885A (en) | Order allocation method and device | |
| Lin et al. | Impacts of two-stage deterioration on an integrated inventory model under trade credit and variable capacity utilization | |
| CN111401619A (en) | Purchase order processing method and device, electronic equipment and storage medium | |
| CN110390501A (en) | Data processing method and its system, computer system and computer-readable medium | |
| CN112017006B (en) | Information pushing method and device, electronic equipment and storage medium | |
| CN110147974A (en) | Inventory's sharing method and device between distributed warehouse | |
| CN110390449A (en) | Warehouse replenishing method and device | |
| CN109523314B (en) | Supply chain management and control method based on AI technology, system and storage medium thereof | |
| KR20220045407A (en) | Ai-based cold chain logistics management system and method | |
| KR102503198B1 (en) | Device and method for providing optimal cargo delivery route based on artificial intelligence | |
| CN110390497A (en) | Article storage method and device | |
| CN115700672A (en) | Cargo transportation mode determining method, device, equipment and storage medium | |
| CN107689123A (en) | Box for material circulation good selling method, device and box for material circulation | |
| CN117236824A (en) | Logistics scheduling method for agricultural product online transaction platform | |
| CN112766868A (en) | Logistics vehicle distribution order matching method and device and computer equipment | |
| CN112308475B (en) | Customs clearance system, customs clearance method, customs clearance device and electronic equipment | |
| CN109902980A (en) | Method and device for business processing | |
| CN117273603A (en) | Warehouse inventory resource management method, device, equipment and storage medium | |
| CN112330235A (en) | Data processing method and device for inventory management, electronic equipment and medium | |
| CN116681363A (en) | Order information processing method and equipment | |
| CN116629735A (en) | Logistics distribution method, logistics distribution device and electronic equipment | |
| CN110363558A (en) | A kind of method and apparatus generating commodity association message | |
| CN114037495A (en) | Order processing method and processor | |
| CN115687908A (en) | Method, device, equipment and storage medium for evaluating site selection scheme of network point | |
| CN108288183A (en) | Ideal money returning method, device and readable storage medium storing program for executing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |