CN114429333A - Logistics planning method, equipment, device and storage medium - Google Patents
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Abstract
The invention discloses a logistics planning method, equipment, a device and a storage medium, wherein the method comprises the following steps: acquiring the leveling requirement of the object flow, and judging whether the leveling requirement of the object flow comprises the leveling requirement of the cargo volume and the position; if the cargo level leveling requirements do not include the cargo level and position leveling requirements, acquiring order information of the order of each pick-up point, and splitting the order into a plurality of sub-orders according to the order information; and performing path optimization on the sub-bill delivery process based on the partition information. Can compromise commodity circulation supply chain's efficiency and commodity circulation cost of transportation through this application.
Description
Technical Field
The invention relates to the technical field of logistics, in particular to a logistics planning method, equipment, a device and a storage medium.
Background
The market environment that domestic automobile manufacturing enterprises face at present is more and more complicated changeable, and the trade competition is more and more intense, and the pressure that inside cost optimization and managerial efficiency promote is bigger and bigger. How to optimize and improve the management efficiency of the internal supply chain and flexibly and quickly face to complex internal and external competition and environmental pressure is an important subject faced by most domestic automobile manufacturing enterprises.
From the current situation, new logistics intelligent technologies (internet of things, big data and the like) are mature day by day, logistics express enterprises such as Jingdong, Shunfeng, vegetable and bird and the like are led in and practiced first, and a high-efficiency and high-quality intelligent logistics supply chain sample plate is created. Against the automobile industry, the intelligent development of a supply chain is still not as advanced as the logistics express industry, and the overall efficiency of the intelligent logistics development is relatively low. The problems of low logistics efficiency, high cost and the like of the existing automobile manufacturing enterprises are caused.
In addition, after the leveling of the logistics of the automobile manufacturing enterprise is incorporated into the logistics plan, the time for incorporating the production parts of each finished automobile is determined according to the production plan due to the leveling production requirement; therefore, it is required that the production of the parts is completed within a prescribed time from the supplier and the transportation is completed using a prescribed route; meanwhile, in order to create a more competitive logistics supply chain, the maximum loading capacity of the parts during transportation needs to be fully considered, the number of transportation passes is reduced as much as possible, and the logistics transportation cost is reduced. However, in the current market, logistics planning system logic which considers both logistics standardization and transportation cost does not exist.
Disclosure of Invention
The invention provides a logistics planning method, equipment, a device and a storage medium, and aims to solve the technical problem that logistics of automobile manufacturing enterprises cannot give consideration to both efficiency and transportation cost.
In order to achieve the above object, the present invention provides a logistics planning method, which comprises the following steps:
acquiring the leveling requirement of the object flow, and judging whether the leveling requirement of the object flow comprises the leveling requirement of the cargo volume and the position;
if the cargo level leveling requirements do not include the cargo level and position leveling requirements, acquiring order information of the order of each pick-up point, and splitting the order into a plurality of sub-orders according to the order information; and performing path optimization on the sub-bill delivery process based on the partition information.
Optionally, if the logistics leveling requirement includes a cargo quantity and a location leveling requirement, performing path optimization on the order delivery process based on the partition information.
Optionally, position information and volume information of the goods pick-up points are obtained, and the goods pick-up points are divided into areas according to the position information and the volume information of the goods to obtain partition information.
Optionally, obtaining transport vehicle information, wherein the transport vehicle information includes a vehicle type of a carrier;
acquiring the maximum volume of the vehicle according to the vehicle type;
and splitting the order into a plurality of sub-orders according to the order cargo area and the maximum volume.
Optionally, acquiring the sub-order cargo volumes of the sub-orders, and sequentially judging whether the sub-order cargo volumes of the plurality of sub-orders are larger than the maximum volume;
and if the sub-order cargo volume of the sub-orders is larger than the maximum volume, further splitting the sub-orders larger than the maximum volume.
Optionally, performing iterative optimization on the initial transportation route according to the partition information through a heuristic algorithm to obtain a plurality of local optimal transportation routes;
scoring the plurality of locally optimal transportation routes and selecting an optimal transportation route from the plurality of locally optimal transportation routes based on the scoring result.
Optionally, transportation costs of the plurality of local optimal transportation routes are respectively obtained, and the plurality of local optimal transportation routes are respectively scored according to the transportation costs.
In order to achieve the above object, the present application further provides a logistics planning apparatus, which includes: the system comprises a leveling demand judging module and an order splitting and path optimizing module, wherein the leveling demand judging module is used for acquiring leveling demands of an object flow and judging whether the leveling demands of the object flow include the demand of leveling the cargo quantity and the position; the order splitting and path optimizing module is used for acquiring order information of orders of all goods taking points if the logistics standardized requirements do not include the cargo volume and position standardized requirements, and splitting the orders into a plurality of sub-orders according to the order information; and performing path optimization on the sub-bill delivery process based on the partition information.
In order to achieve the above object, the present application further provides a logistics planning apparatus, which includes a memory, a processor, and a logistics planning program stored in the memory and operable on the processor, wherein the logistics planning program, when executed by the processor, implements the logistics planning method.
In order to achieve the above object, the present application further provides a computer-readable storage medium, in which a logistics planning program is stored, and the logistics planning program, when executed by a processor, implements the logistics planning method.
This application is through considering respectively obtaining the thing flow standardization demand, judge whether including goods volume and position standardization demand in the thing flow standardization demand, and consider respectively not including under the circumstances of goods volume and position standardization demand in the commodity flow standardization demand, carry out route optimization with the order split for a plurality of submenus and the transportation process of submenu, including under the circumstances of goods volume and position standardization demand in the commodity flow standardization demand, directly carry out route optimization to the process that the order was transported, therefore, compare with prior art, this application adopts different transportation strategies under the standardization demand of difference, logistics efficiency and cost of transportation have been compromise.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
Fig. 1 is a schematic block diagram of a logistics planning method according to an embodiment of the invention;
FIG. 2 is a flow chart of a logistics planning method according to an embodiment of the present invention;
fig. 3 is a schematic block structure diagram of a logistics planning method according to an embodiment of the invention.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic diagram of a hardware structure of a logistics planning apparatus provided in each embodiment of the present invention. The logistics planning device comprises an execution module 01, a memory 02, a processor 03, a battery system and the like. Those skilled in the art will appreciate that the apparatus shown in fig. 1 may also include more or fewer components than those shown, or combine certain components, or a different arrangement of components. The processor 03 is connected to the memory 02 and the execution module 01, respectively, a logistics planning program is stored in the memory 02, and the logistics planning program is executed by the processor 03 at the same time.
The execution module 01 can acquire the logistics leveling requirements and judge whether the logistics leveling requirements include the cargo quantity and position leveling requirements; if the logistics leveling requirements do not include the cargo quantity and position leveling requirements, acquiring order information of the orders of the pickup points, and splitting the orders into a plurality of sub-orders according to the order information; and performing path optimization on the process of the sub-bill delivery based on the partition information. And simultaneously feeds back the above information to the processor 03.
The memory 02 may be used to store software programs and various data. The memory 02 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for a plurality of functions, and the like; the storage data area may store data or information created according to the use of the internet of things terminal, or the like. Further, the memory 02 may include high speed random access memory, and may also include non-volatile memory, such as a plurality of magnetic disk storage devices, flash memory devices, or other volatile solid state storage devices.
The processor 03, which is a control center of the processing platform, is connected to each part of the whole internet of things terminal by using various interfaces and lines, and executes various functions and processing data of the internet of things terminal by running or executing software programs and/or modules stored in the memory 02 and calling data stored in the memory 02, thereby integrally monitoring the logistics planning equipment. Processor 03 may include one or more processing units; preferably, the processor 03 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 03.
Those skilled in the art will appreciate that the logistics planning apparatus configuration shown in fig. 1 does not constitute a limitation of the apparatus and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
Various embodiments of the method of the present invention are presented in terms of the above-described hardware architecture.
The market environment that domestic automobile manufacturing enterprises face at present is more and more complicated changeable, and the trade competition is more and more intense, and the pressure that inside cost optimization and managerial efficiency promote is bigger and bigger. How to optimize and improve the management efficiency of the internal supply chain and flexibly and quickly face to complex internal and external competition and environmental pressure is an important subject faced by most domestic automobile manufacturing enterprises.
From the current situation, new logistics intelligent technologies (internet of things, big data and the like) are mature day by day, logistics express enterprises such as Jingdong, Shunfeng, vegetable and bird and the like are led in and practiced first, and a high-efficiency and high-quality intelligent logistics supply chain sample plate is created. Against the automobile industry, the intelligent development of a supply chain is still not as advanced as the logistics express industry, and the overall efficiency of the intelligent logistics development is relatively low. Resulting in the problems of low logistics efficiency, high cost and the like of the existing automobile manufacturing enterprises.
Specifically, in the prior art, the production of the automobile manufacturing enterprises has the characteristic of leveling, so-called leveling production is a production plan for evenly distributing production tasks from the aspects of both yield and product combination, and products are not produced according to customer orders which may have fluctuating heights and falls. And the part logistics are production service, and if the production requirement is standardized, the goods taking and delivery of the logistics are arranged according to the standardized production. At present, no existing or developing logistics planning system for production parts in the market covers or relates to a 'leveling' function, so that no method which can be directly used in an automobile manufacturing enterprise exists, and a logistics planning system logic which meets the leveling requirement needs to be newly constructed.
In addition, after the leveling of the logistics of the automobile manufacturing enterprise is incorporated into the logistics plan, the time for incorporating the production parts of each finished automobile is determined according to the production plan due to the leveling production requirement; therefore, it is required that the production of the parts is completed within a prescribed time from the supplier and the transportation is completed using a prescribed route; meanwhile, in order to create a more competitive logistics supply chain, the maximum loading capacity of the parts during transportation needs to be fully considered, the number of transportation passes is reduced as much as possible, and the logistics transportation cost is reduced.
However, in the current market, logistics planning system logic which considers both logistics standardization and transportation cost does not exist.
In order to solve the above problem, the present application provides a logistics planning method, and referring to fig. 2, in a first embodiment of the logistics planning method of the present invention, the logistics planning method includes:
step S100, acquiring a logistics leveling requirement, and judging whether the logistics leveling requirement comprises a cargo quantity and position leveling requirement;
in this embodiment, the stream leveling can be split into position leveling, cargo quantity leveling, and time leveling. The position leveling refers to that goods need to be picked from the same part supplier in the same order every time in the same line group; the quantity standardization refers to that in the same route group, the goods which are taken from the same part supplier at each time need to be the same type of goods with the same quantity; the time-flattening refers to that the time intervals in the same line group are equal.
The 'leveling' considered by the system comprises three conditions: firstly, complete leveling, namely leveling of positions and cargo volumes and leveling of time are met; secondly, the position and the cargo quantity are required to be leveled, and the time is not required to meet the leveling; thirdly, the leveling principle is not required to be met, and the position, the cargo quantity and the time are not required to be met. The concrete adopted leveling situation depends on the logistics leveling requirements of users.
The time leveling is irrelevant to the loading process, and only the cargo quantity and the position leveling influence the loading process of the order, so that whether the cargo quantity and the position leveling requirements are included in the object flow leveling requirements or not is judged.
Step S200, if the cargo level leveling requirements do not include the cargo level and position leveling requirements, acquiring order information of each pick-up point order, and splitting the order into a plurality of sub-orders according to the order information; and performing path optimization on the sub-bill delivery process based on the partition information.
In an embodiment, the step of determining whether the leveling requirement of the object flow includes a leveling requirement of a cargo volume and a location includes the following steps:
and if the object flow leveling requirements comprise the cargo quantity and position leveling requirements, performing path optimization on the order delivery process based on partition information.
In this embodiment, if the logistics leveling requirements include the demand for leveling the quantity of goods and the location, that is, in the logistics process, in the same line group, every time, the goods need to be picked up from the same part supplier in the same order; and each time the goods are taken from the same part supplier, the goods need to be the same kind of goods with the same goods quantity; in this case, since strict requirements are imposed on the cargo level and the position level, the order cannot be split, and the route optimization can be directly performed on the order delivery process based on the partition information.
If the cargo quantity and position leveling requirements are not included in the object flow leveling requirements, the order information of the order can be obtained, the order is divided into a plurality of sub-orders according to the order information, and then path optimization is carried out on the sub-orders based on the partition information.
This application is through considering respectively obtaining the thing flow standardization demand, judge whether including goods volume and position standardization demand in the thing flow standardization demand, and consider respectively not including under the circumstances of goods volume and position standardization demand in the commodity flow standardization demand, carry out route optimization with the order split for a plurality of submenus and the transportation process of submenu, including under the circumstances of goods volume and position standardization demand in the commodity flow standardization demand, directly carry out route optimization to the process that the order was transported, therefore, compare with prior art, this application adopts different transportation strategies under the standardization demand of difference, logistics efficiency and cost of transportation have been compromise.
In one embodiment, the step of obtaining the leveling requirement of the object flow comprises:
and acquiring position information and volume information of the goods at the goods pick-up points, and carrying out region division on the goods pick-up points according to the position information and the volume information of the goods at the goods pick-up points to obtain partition information.
In this embodiment, before performing route optimization, the pick-up point of the supplier needs to be divided into a plurality of areas. Specifically, the suppliers are split into multiple regions according to the prior knowledge and spatial clustering of the optimization objective. In the aspect of driving mileage, the pickup points with similar spatial positions are mainly divided into subareas, so that the loading rate of the driving mileage can be effectively reduced, and the loading rate of the subareas can be effectively improved by mainly considering that the order goods volume of the pickup points in the same subarea is closer to the integral multiple of the vehicle loading capacity. And by considering the spatial position and the loading rate, a clustering method is adopted to realize the function of region division.
Furthermore, in one embodiment, the pick-up points within the same preset range size are divided into a first area according to the pick-up point position information; the goods picking point position information comprises a goods picking point position which refers to a position where a supplier for picking goods is located; the predetermined range may be a circle with any radius or a square or rectangle with any size, and the size and shape of the range are not limited in the present invention. Specifically, the pick-up points in the same circle, square or rectangle are divided into first areas. It should be noted that there may be a plurality of the first regions.
After the position information of the goods picking points is obtained, calculating the total volume of goods of all the goods picking points in the first area according to the goods picking point goods volume information; the pick-up point goods volume information comprises the total volume of the pick-up point goods and the volume of the single goods of the pick-up point. In this embodiment, the total volume of the goods at the pick-up point in the first area may be added to obtain the total volume of the goods.
Then, the number of the goods picking points in the first area can be changed according to the total goods volume and the preset vehicle loading capacity, and the maximum loading rate in the first area is calculated; in the present embodiment, the preset vehicle load amount refers to the total load amount of the transportation vehicles, for example, when there is one transportation vehicle, the total load amount is the load amount of one transportation vehicle; when there are 3 transport vehicles, the overall load is the load of 3 transport vehicles. Changing the number of pick-up points in the first area refers to increasing or decreasing the number of pick-up points at the boundary of the first area, namely, putting the pick-up points at the boundary into other adjacent areas, or adding the pick-up points from the adjacent areas into the first area. The maximum loading rate in the first region is calculated once every time the number of the pickup points is increased or decreased once, specifically, the multiple of the total volume of the goods in the first region and the preset vehicle loading capacity, that is, the difference between the total volume of the goods and the preset vehicle loading capacity is calculated, and when the total volume of the goods is closer to the integral multiple of the preset vehicle loading capacity, the loading rate is larger.
Finally, the first region corresponding to the maximum loading rate may be set as the target divided region. In this embodiment, when the maximum loading rate in the first area is larger, it indicates that the vehicle can be filled with the vehicle in every transportation, so that the maximum loading rate of the vehicle is ensured, the waste of transportation resources is avoided, and the cost is reduced. The target division area is an area for transporting and picking up the goods by the vehicle, and the target division area can be a plurality of target division areas.
In an embodiment, the order information includes an order cargo volume, and the step of splitting the order into a plurality of sub-orders according to the order information includes:
acquiring transportation vehicle information, wherein the transportation vehicle information comprises a vehicle type of a transport provider;
acquiring the maximum volume of the vehicle according to the vehicle type;
and splitting the order into a plurality of sub-orders according to the order cargo area and the maximum volume.
In this embodiment, if the order needs to be split, before optimizing the path of the cargo transportation, the very large splitting module needs to be called first, and the order with the cargo volume exceeding the maximum vehicle type volume in the goods to be extracted is split into a plurality of sub-orders which can be assembled and disassembled in the maximum vehicle type to be loaded respectively.
Specifically, all orders have corresponding order information, the order information at least comprises identification numbers of suppliers, order goods volumes and carrier vehicle type limits, the carrier vehicle information at least comprises vehicle types of all carriers in a logistics plan, the maximum volume of the vehicle can be obtained according to the vehicle types, then the maximum volume of the vehicle is compared with the order goods volumes in the order information, and the orders are split into a plurality of sub-orders according to comparison results.
Further, if all the goods in the order are smaller than or equal to the maximum volume of the vehicle, the order does not need to be split, and if the goods in the order are larger than the maximum volume of the vehicle, the order needs to be split into a plurality of sub-orders according to a preset splitting rule, wherein the preset splitting rule is set in advance by a person skilled in the art, and can be adjusted in real time according to specific requirements.
In one embodiment, the step of splitting the order into a plurality of sub-orders according to the order cargo volume and the maximum volume is followed by:
acquiring the sub-order cargo volume of the sub-orders, and sequentially judging whether the sub-order cargo volume of the plurality of sub-orders is larger than the maximum volume;
and if the sub-order cargo volume of the sub-orders is larger than the maximum volume, further splitting the sub-orders larger than the maximum volume.
In this embodiment, after the order is split according to the preset rule and the order information, it is further necessary to further determine whether the sub-order needs to be further split, that is, the sub-order cargo volume of the sub-order is compared with the maximum volume of the vehicle, if the sub-order cargo volumes of the sub-order are all smaller than or equal to the maximum volume of the vehicle, the sub-order does not need to be further split, so as to avoid that the order is split into pieces, and if the sub-order cargo volume of the sub-order is larger than the maximum volume of the vehicle, the sub-orders need to be further split, so as to improve the loading rate of the vehicle.
In an embodiment, the step of optimizing the path of the sub-bill delivery process based on the partition information includes:
performing iterative optimization on the initial transportation route according to the partition information through a heuristic algorithm to obtain a plurality of local optimal transportation routes;
scoring the plurality of locally optimal transportation routes and selecting an optimal transportation route from the plurality of locally optimal transportation routes based on the scoring result.
In this embodiment, if the logistics leveling needs to meet the location and cargo leveling, iterative optimization needs to be performed on the initial transportation route according to the partition information to obtain a plurality of local optimal transportation routes. The method comprises the steps of firstly carrying out picking point grouping according to the maximum loading rate in a region to obtain a plurality of partition information, then determining distribution times according to the partition information, secondly carrying out route planning according to the geographical position of each picking point by taking the minimum mileage as a target, finally comprehensively evaluating the cost of output results, searching for a better route group based on a self-research operation optimization solver, and carrying out iterative optimization. Wherein, the local optimal transportation route refers to the transportation route with the lowest cost when only part of suppliers in the transportation route or part of logistics influence parameters are considered.
Further, in an embodiment, a specific iterative optimization process is as follows: and performing optimization search by adopting a domain search algorithm, designing record update of the intermediate result state by adopting an ant colony algorithm pheromone record update method, and jumping out of a local optimal transportation route by adopting a delay receiving algorithm. Wherein the intermediate result state comprises material flow influence parameters, such as loading rate and the like.
After the plurality of local optimal transportation routes are obtained, the optimal transportation routes are scored by calling a scoring module, and the local optimal transportation route with the highest score is selected from the plurality of local optimal transportation routes according to a scoring result to serve as the optimal transportation route.
In one embodiment, the step of scoring a plurality of the locally optimal transportation routes comprises:
and respectively obtaining the transportation cost of the local optimal transportation routes, and respectively scoring the local optimal transportation routes according to the transportation cost.
In this embodiment, the transportation cost is a unique evaluation criterion for measuring the score corresponding to each local optimal transportation route, that is, the lower the transportation cost is, the higher the score corresponding to the local optimal transportation route is; the lower the transportation cost, the lower the score corresponding to the locally optimal transportation route. Because the plurality of local optimal transportation routes all meet the demand of the leveling of the cargo quantity and the position, the local optimal transportation route with the highest score is the transportation route with the lowest cost which meets the demand of the leveling of the cargo quantity and the position. And in the process of scoring each local optimal transportation route based on the transportation cost, different calculations are carried out on the transportation cost according to different unloading points.
Specifically, if the unloading point is a relay, such as a storage warehouse, the transportation cost is equal to the hard cost in the logistics transportation process; if the point of discharge is a physical entry point, such as a manufacturing plant, the cost of transportation is equal to the sum of the hard cost and the soft cost of the logistics transportation process.
As shown in fig. 3, the present invention further provides a logistics planning apparatus, which includes:
the leveling requirement judging module A10 is used for acquiring a logistics leveling requirement and judging whether the logistics leveling requirement comprises a cargo quantity and position leveling requirement;
the order splitting and path optimizing module A20 is used for acquiring order information of orders of each pickup point if the logistics standardized demand does not include the demand for cargo volume and position standardized demand, and splitting the orders into a plurality of sub-orders according to the order information; and performing path optimization on the sub-bill delivery process based on the partition information.
The invention further provides logistics planning equipment, which comprises a memory, a processor and a logistics planning program stored on the memory and capable of running on the processor, wherein the logistics planning program is used for executing the method of each embodiment of the invention.
The invention also proposes a computer-readable storage medium on which a logistics planning program is stored. The storage medium includes a computer-readable storage medium, which may be the Memory in fig. 1, and may also be at least one of a ROM (Read-Only Memory)/RAM (Random Access Memory), a magnetic disk, and an optical disk, where the storage medium includes several instructions to enable an internet of things terminal device (which may be a mobile phone, a computer, a server, an internet of things terminal, or a network device) having a processor to execute the method according to each embodiment of the present invention.
In the present invention, the terms "first", "second", "third", "fourth" and "fifth" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance, and it is obvious to those skilled in the art that the above-mentioned terms have specific meanings in the present invention according to specific situations.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in multiple embodiments or examples of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although the embodiment of the present invention has been shown and described, the scope of the present invention is not limited thereto, it should be understood that the above embodiment is illustrative and not to be construed as limiting the present invention, and that those skilled in the art can make changes, modifications and substitutions to the above embodiment within the scope of the present invention, and that these changes, modifications and substitutions should be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method of logistics planning, said method comprising the steps of:
acquiring the leveling requirement of the object flow, and judging whether the leveling requirement of the object flow comprises the leveling requirement of the cargo volume and the position;
if the cargo level leveling requirements do not include the cargo level and position leveling requirements, acquiring order information of the order of each pick-up point, and splitting the order into a plurality of sub-orders according to the order information; and performing path optimization on the sub-bill delivery process based on the partition information.
2. The method for logistics planning as defined in claim 1 wherein said step of determining whether said logistics leveling requirements include load leveling and location leveling requirements is followed by the steps of:
and if the object flow leveling requirements comprise the cargo quantity and position leveling requirements, performing path optimization on the order delivery process based on the partition information.
3. The logistics planning method of claim 1 wherein said step of obtaining the leveling requirements of the stream is preceded by:
and acquiring position information and volume information of the goods picking points, and carrying out region division on the goods picking points according to the position information and the volume information of the goods at the goods picking points to obtain partition information.
4. The logistics planning method of claim 1, wherein said order information comprises an order cargo volume, and said step of splitting said order into a plurality of sub-orders based on said order information comprises:
acquiring transportation vehicle information, wherein the transportation vehicle information comprises a vehicle type of a transport provider;
acquiring the maximum volume of the vehicle according to the vehicle type;
and splitting the order into a plurality of sub-orders according to the order cargo area and the maximum volume.
5. The logistics planning method of claim 4 wherein said step of splitting said order into a plurality of sub-orders based on said order cargo volume and maximum volume is followed by:
acquiring the sub-order cargo volume of the sub-orders, and sequentially judging whether the sub-order cargo volume of the plurality of sub-orders is larger than the maximum volume;
and if the sub-order cargo volume of the sub-orders is larger than the maximum volume, further splitting the sub-orders larger than the maximum volume.
6. The logistics planning method of claim 1, wherein the step of optimizing the path of the sub-order delivery process based on the partition information comprises:
performing iterative optimization on the initial transportation route according to the partition information through a heuristic algorithm to obtain a plurality of local optimal transportation routes;
scoring the plurality of locally optimal transportation routes and selecting an optimal transportation route from the plurality of locally optimal transportation routes based on the scoring result.
7. The logistics planning method of claim 6, wherein said step of scoring a plurality of said locally optimal transportation routes comprises:
and respectively obtaining the transportation cost of the local optimal transportation routes, and respectively scoring the local optimal transportation routes according to the transportation cost.
8. A logistics planning apparatus, comprising:
the leveling demand judging module is used for acquiring a logistics leveling demand and judging whether the logistics leveling demand comprises a cargo quantity and position leveling demand;
the order splitting and path optimizing module is used for acquiring order information of orders of all the pickup points if the logistics standardized demand does not include the cargo volume and position standardized demand, and splitting the orders into a plurality of sub-orders according to the order information; and performing path optimization on the sub-bill delivery process based on the partition information.
9. A logistics planning apparatus comprising a memory, a processor, and a logistics planning program stored on the memory and executable on the processor, the logistics planning program when executed by the processor implementing the steps of the logistics planning method of any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the storage medium has stored thereon a logistics planning program, which when executed by a processor implements the steps of the logistics planning method according to any one of claims 1 to 7.
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