Intelligent algorithm for solving a multi-objective MDVRPTW (Multi-Depot Vehicle Routing Problem with Time Window)

A technology of vehicle routing problem and intelligent algorithm, which is applied in the field of intelligent algorithm for solving multi-objective multi-parking vehicle routing problem with time window, and can solve problems with high difficulty

Inactive Publication Date: 2017-05-10
SUN YAT SEN UNIV +1
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

In this problem, the existence of multiple parking lots and the existence of customer time windows make the solution of the problem more difficult than the VRP problem

Method used

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  • Intelligent algorithm for solving a multi-objective MDVRPTW (Multi-Depot Vehicle Routing Problem with Time Window)
  • Intelligent algorithm for solving a multi-objective MDVRPTW (Multi-Depot Vehicle Routing Problem with Time Window)
  • Intelligent algorithm for solving a multi-objective MDVRPTW (Multi-Depot Vehicle Routing Problem with Time Window)

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Embodiment 1

[0053]In multi-objective MDVRPTW, each vehicle departs from a depot, and finally returns to the depot after serving a certain number of customers. Vehicles have a fixed capacity limit, and each customer has a fixed service demand and service time window. Since the soft time window is beneficial to cost optimization, reasonable delay of customer service time is allowed in this MDVRTTW model. In this algorithm, all solutions are required to be legal solutions.

[0054] Figure 1-2 Shown is a solution and its encoded representation. Each parking lot has several paths, and the rth path of the dth parking lot is expressed as The set of all paths is denoted as R, and the set of all paths of the d-th parking lot is R d , the set of all parking lots is denoted as D. In this multi-objective MDVRPTW model, the optimization objective is

[0055] min F=(f 1 , f 2 , f 3 , f 4 , f 5 )

[0056] What each goal represents and how it is assessed are as follows.

[0057] f 1 is th...

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Abstract

The invention provides an intelligent algorithm for solving a multi-objective MDVRPTW (Multi-Depot Vehicle Routing Problem with Time Window), which comprises: a first step: by combining a non-dominant sorting genetic algorithm with an elitist strategy on the basis of an extreme value crowding distance with local searching, searching an extremal solution in a decision space; and a second step: by combining a multi-objective evolutionary algorithm based on decomposition with local searching, on the basis of a final population solved in the first step, further optimizing to obtain a group of solutions with both convergence and diversity. The two-step process enables convergence and diversity of the algorithm to be well balanced, and promotes quality of solving the multi-objective MDVRPTW by the algorithm.

Description

technical field [0001] The invention relates to the field of logistics scheduling algorithms, and more specifically, relates to an intelligent algorithm for solving multi-objective multi-depot vehicle routing problems with time windows. Background technique [0002] Logistics is the tertiary industry and an important industry related to the country's economic development. Especially with the improvement of living standards and the development of e-commerce, the development of logistics industry has been paid more and more attention. As an important part of logistics distribution, Vehicle Routing Problem (VRP) is a research topic with high practical significance. Among the vehicle routing problems, the multi-depot vehicle routing problem with time windows (MDVRPTW) is an important variant. Many delivery scenarios in real life can be abstracted as MDVRPTW. In this problem, the existence of multiple parking lots and the existence of customer time windows make the solution of...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/08
CPCG06Q10/04G06Q10/08355
Inventor 王甲海翁太耀印鉴
Owner SUN YAT SEN UNIV
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