CN111898830A - Logistics distribution path site selection optimization method and terminal equipment - Google Patents
Logistics distribution path site selection optimization method and terminal equipment Download PDFInfo
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- CN111898830A CN111898830A CN202010775163.2A CN202010775163A CN111898830A CN 111898830 A CN111898830 A CN 111898830A CN 202010775163 A CN202010775163 A CN 202010775163A CN 111898830 A CN111898830 A CN 111898830A
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- 238000009826 distribution Methods 0.000 title claims abstract description 107
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000005457 optimization Methods 0.000 title claims description 17
- 238000013178 mathematical model Methods 0.000 claims abstract description 15
- 230000006870 function Effects 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 2
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0835—Relationships between shipper or supplier and carriers
- G06Q10/08355—Routing methods
Abstract
The invention discloses a method for optimizing a logistics distribution path site selection and a terminal device, comprising the following steps: s1, dividing the urban area to generate a plurality of divided areas, and setting at least one logistics distribution personnel for each divided area; s2, collecting the requirement of the customer for the delivery time, combining the order quantity of the customer point, and constructing an order terminal delivery mathematical model; s3, establishing a Petri network model of a logistics distribution path based on the order terminal distribution mathematical model, and converting the order terminal distribution mathematical model into an integer linear programming problem; s4 receives logistics distribution information, which includes address information. The method can quickly find the optimal route of the vehicle distribution route, and the obtained total distribution route has the shortest distance, thereby ensuring the effect of optimizing the logistics distribution route in the workshop, reducing the logistics cost, improving the production efficiency of the workshop and having good application prospect.
Description
Technical Field
The invention relates to the technical field of path optimization, in particular to a method for optimizing a logistics distribution path site and a terminal device.
Background
In the prior art, the electronic commerce enterprises deliver/take goods for consumers, and the problems of high delivery cost and long time are existed, the advantages of the electronic commerce enterprises are seriously influenced by the problems, and the product delivery becomes a key bottleneck restricting the development of the electronic commerce. Therefore, it is an urgent need to find a logistics distribution method that improves logistics distribution efficiency and saves logistics distribution cost to the maximum extent.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides a logistics distribution path site selection optimization method and terminal equipment.
The invention provides a method for optimizing the site selection of a logistics distribution path, which comprises the following steps:
s1, dividing the urban area to generate a plurality of divided areas, and setting at least one logistics distribution personnel for each divided area;
s2, collecting the requirement of the customer for the delivery time, combining the order quantity of the customer point, and constructing an order terminal delivery mathematical model;
s3, establishing a Petri network model of a logistics distribution path based on the order terminal distribution mathematical model, and converting the order terminal distribution mathematical model into an integer linear programming problem;
s4 receiving logistics distribution information, wherein the logistics distribution information comprises address information, generating logistics distribution tasks according to the logistics distribution information, sending the logistics distribution tasks to the work terminals of logistics distribution personnel corresponding to the address information, and generating corresponding objective functions;
s5, recommending a logistics distribution path through a path optimization algorithm according to the current logistics distribution task of the logistics distribution personnel and the real-time traffic condition and the historical traffic information, and sending the logistics distribution path to the work terminal of the logistics distribution personnel for display.
Preferably, the objective function of step S4 is:
where dij represents the distance between node i and node j, xij is a variable from 0 to 1, and when the planned path passes through the arc (i, j) from node i, xij is 1, otherwise, xij is 0, and dse represents the total distance from the starting point to the target point.
Preferably, the receiving of the logistics distribution time in step S4 is to connect any article with the internet through radio frequency identification, infrared sensor, global positioning system and laser scanner for information exchange and communication.
Preferably, the step S5 includes: taking all logistics distribution tasks as a traveling salesman problem, and solving a plurality of optimal paths; for each preferred path, dividing the preferred path into a plurality of sub-paths according to streets, wherein the plurality of sub-paths form the whole preferred path; calculating the time corresponding to each sub-path through a formula T ═ α ═ T current + (1- α) × T history, and calculating the time corresponding to the whole preferred path according to the calculated time corresponding to each sub-path; wherein T is the corresponding running time of each sub-path under the current traffic condition currently, T history is the corresponding running time of each sub-path under the historical traffic information, and alpha is more than 0 and less than 1; and sequencing the calculated time of each preferred path, and selecting and displaying a plurality of preferred paths with the shortest time.
Preferably, the step S4 is configured to receive the logistics distribution information, and the distribution task generating module is configured to receive the logistics distribution information.
Preferably, the requirements of the customers on the delivery time are collected, and a customer satisfaction objective function which changes with time of each customer point is obtained by applying a customer satisfaction objective function formula.
Terminal device of a method for optimizing logistics distribution route addressing, comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor, when executing said computer program, implements the steps of the method according to any of claims 1 to 6.
According to the logistics distribution path site selection optimization method and the terminal equipment, the optimal path of the vehicle distribution path can be quickly found, the obtained total distribution path distance is shortest, the effect of optimizing the logistics distribution path in a workshop is guaranteed, the logistics cost is reduced, the workshop production efficiency is improved, and the method and the terminal equipment have good application prospects.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments.
The logistics distribution path site selection optimization method comprises the following steps:
s1, dividing the urban area to generate a plurality of divided areas, and setting at least one logistics distribution personnel for each divided area;
s2, collecting the requirement of the customer for the delivery time, combining the order quantity of the customer point, and constructing an order terminal delivery mathematical model;
s3, establishing a Petri network model of a logistics distribution path based on the order terminal distribution mathematical model, and converting the order terminal distribution mathematical model into an integer linear programming problem;
s4 receiving logistics distribution information, wherein the logistics distribution information comprises address information, generating logistics distribution tasks according to the logistics distribution information, sending the logistics distribution tasks to the work terminals of logistics distribution personnel corresponding to the address information, and generating corresponding objective functions;
s5, recommending a logistics distribution path through a path optimization algorithm according to the current logistics distribution task of the logistics distribution personnel and the real-time traffic condition and the historical traffic information, and sending the logistics distribution path to the work terminal of the logistics distribution personnel for display.
In the present invention, the objective function of step S4 is:
where dij represents the distance between node i and node j, xij is a variable from 0 to 1, and when the planned path starts from node i through the arc (i,j) when xij is 1, otherwise xij is 0, dse represents the total distance from the starting point to the target point.
In the present invention, the receiving logistics distribution time in step S4 is performed by connecting any article to the internet through radio frequency identification, infrared sensor, global positioning system, and laser scanner, so as to exchange and communicate information.
In the present invention, the step S5 includes: taking all logistics distribution tasks as a traveling salesman problem, and solving a plurality of optimal paths; for each preferred path, dividing the preferred path into a plurality of sub-paths according to streets, wherein the plurality of sub-paths form the whole preferred path; calculating the time corresponding to each sub-path through a formula T ═ α ═ T current + (1- α) × T history, and calculating the time corresponding to the whole preferred path according to the calculated time corresponding to each sub-path; wherein T is the corresponding running time of each sub-path under the current traffic condition currently, T history is the corresponding running time of each sub-path under the historical traffic information, and alpha is more than 0 and less than 1; and sequencing the calculated time of each preferred path, and selecting and displaying a plurality of preferred paths with the shortest time.
In the present invention, the step S4 is configured to receive logistics distribution information, and the distribution task generating module is configured to receive logistics distribution information.
In the invention, the requirements of customers on the distribution time are collected, and a customer satisfaction objective function of each customer point changing along with the time is obtained by using a customer satisfaction objective function formula.
Terminal device of a method for optimizing logistics distribution route addressing, comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor, when executing said computer program, implements the steps of the method according to any of claims 1 to 6.
The invention comprises the following steps: dividing an urban area to generate a plurality of divided areas, and setting at least one logistics distribution worker for each divided area; collecting the requirement of a client on delivery time, combining the order quantity of a client point, and constructing an order terminal delivery mathematical model; establishing a Petri network model of a logistics distribution path based on the order terminal distribution mathematical model, and converting the order terminal distribution mathematical model into an integer linear programming problem; receiving logistics distribution information, wherein the logistics distribution information comprises address information, generating a logistics distribution task according to the logistics distribution information, sending the logistics distribution task to a work terminal of a logistics distribution worker corresponding to the address information, and generating a corresponding objective function; and recommending a logistics distribution path through a path optimization algorithm according to the current logistics distribution task of the logistics distribution personnel and the real-time traffic condition and the historical traffic information, and sending the logistics distribution path to a work terminal of the logistics distribution personnel for displaying.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (7)
1. The logistics distribution path site selection optimization method is characterized by comprising the following steps:
s1, dividing the urban area to generate a plurality of divided areas, and setting at least one logistics distribution personnel for each divided area;
s2, collecting the requirement of the customer for the delivery time, combining the order quantity of the customer point, and constructing an order terminal delivery mathematical model;
s3, establishing a Petri network model of a logistics distribution path based on the order terminal distribution mathematical model, and converting the order terminal distribution mathematical model into an integer linear programming problem;
s4 receiving logistics distribution information, wherein the logistics distribution information comprises address information, generating logistics distribution tasks according to the logistics distribution information, sending the logistics distribution tasks to the work terminals of logistics distribution personnel corresponding to the address information, and generating corresponding objective functions;
s5, recommending a logistics distribution path through a path optimization algorithm according to the current logistics distribution task of the logistics distribution personnel and the real-time traffic condition and the historical traffic information, and sending the logistics distribution path to the work terminal of the logistics distribution personnel for display.
2. The logistics distribution path site selection optimization method of claim 1, wherein the objective function of the step S4 is:
where dij represents the distance between node i and node j, xij is a variable from 0 to 1, and when the planned path passes through the arc (i, j) from node i, xij is 1, otherwise, xij is 0, and dse represents the total distance from the starting point to the target point.
3. The logistics distribution route site selection optimization method of claim 1, wherein the logistics distribution time received in step S4 is any item connected to the internet through radio frequency identification, infrared sensor, global positioning system and laser scanner for information exchange and communication.
4. The logistics distribution path site selection optimization method of claim 1, wherein the step S5 comprises: taking all logistics distribution tasks as a traveling salesman problem, and solving a plurality of optimal paths; for each preferred path, dividing the preferred path into a plurality of sub-paths according to streets, wherein the plurality of sub-paths form the whole preferred path; calculating the time corresponding to each sub-path through a formula T ═ α ═ T current + (1- α) × T history, and calculating the time corresponding to the whole preferred path according to the calculated time corresponding to each sub-path; wherein T is the corresponding running time of each sub-path under the current traffic condition currently, T history is the corresponding running time of each sub-path under the historical traffic information, and alpha is more than 0 and less than 1; and sequencing the calculated time of each preferred path, and selecting and displaying a plurality of preferred paths with the shortest time.
5. The logistics distribution path site selection optimization method of claim 1, wherein the step S4 is configured to receive the logistics distribution information by using a distribution task generating module.
6. The logistics distribution path site selection optimization method of claim 1, wherein the customer requirements for distribution time are collected and a customer satisfaction objective function formula is applied to obtain a customer satisfaction objective function of each customer point changing with time.
7. Terminal device of a method for optimization of logistics distribution route addressing, comprising a memory, a processor and a computer program stored in said memory and executable on said processor, wherein said processor when executing said computer program implements the steps of the method according to any of claims 1 to 6.
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| CN202010775163.2A CN111898830A (en) | 2020-08-04 | 2020-08-04 | Logistics distribution path site selection optimization method and terminal equipment |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117436776A (en) * | 2023-12-19 | 2024-01-23 | 广东鑫港湾供应链管理有限公司 | Supply chain intelligent logistics distribution management system |
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| CN104156843A (en) * | 2014-08-08 | 2014-11-19 | 上海新跃物流企业管理有限公司 | Logistics distribution management system and logistics distribution management method |
| CN105894222A (en) * | 2014-12-16 | 2016-08-24 | 重庆邮电大学 | Logistics distribution path optimization method |
| CN108573325A (en) * | 2018-04-16 | 2018-09-25 | 哈尔滨工业大学 | Logistics distribution method for optimizing route and terminal device |
| CN111325389A (en) * | 2020-02-17 | 2020-06-23 | 陕西科技大学 | Vehicle path optimization method based on Petri network and integer linear programming |
| CN111445186A (en) * | 2020-03-27 | 2020-07-24 | 陕西科技大学 | Petri network theory-based vehicle path optimization method with time window |
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2020
- 2020-08-04 CN CN202010775163.2A patent/CN111898830A/en active Pending
Patent Citations (5)
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| CN104156843A (en) * | 2014-08-08 | 2014-11-19 | 上海新跃物流企业管理有限公司 | Logistics distribution management system and logistics distribution management method |
| CN105894222A (en) * | 2014-12-16 | 2016-08-24 | 重庆邮电大学 | Logistics distribution path optimization method |
| CN108573325A (en) * | 2018-04-16 | 2018-09-25 | 哈尔滨工业大学 | Logistics distribution method for optimizing route and terminal device |
| CN111325389A (en) * | 2020-02-17 | 2020-06-23 | 陕西科技大学 | Vehicle path optimization method based on Petri network and integer linear programming |
| CN111445186A (en) * | 2020-03-27 | 2020-07-24 | 陕西科技大学 | Petri network theory-based vehicle path optimization method with time window |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117436776A (en) * | 2023-12-19 | 2024-01-23 | 广东鑫港湾供应链管理有限公司 | Supply chain intelligent logistics distribution management system |
| CN117436776B (en) * | 2023-12-19 | 2024-03-29 | 广东鑫港湾供应链管理有限公司 | Supply chain intelligent logistics distribution management system |
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Application publication date: 20201106 |