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Variable neighborhood search algorithm for solving multi depot vehicle routing problem with time windows

A technology of vehicle routing problem and variable neighborhood search, applied in the field of operations research, can solve problems such as lack of generality, and achieve the effect of enhancing the optimization effect

Inactive Publication Date: 2013-01-16
LANGCHAO ELECTRONIC INFORMATION IND CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At the same time, meta-heuristic algorithms usually need to set more empirical parameters, and these parameters often need to be set according to specific problems, which do not have strong versatility

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  • Variable neighborhood search algorithm for solving multi depot vehicle routing problem with time windows
  • Variable neighborhood search algorithm for solving multi depot vehicle routing problem with time windows
  • Variable neighborhood search algorithm for solving multi depot vehicle routing problem with time windows

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Embodiment Construction

[0031] The algorithm of the present invention will be described in detail below with reference to the accompanying drawings.

[0032] The basic flowchart of this algorithm model, such as figure 1 shown. The technical solution of the present invention will be described below in conjunction with each step in the flow chart.

[0033] (1) The multi-depot vehicle routing problem with time windows is limited by the vehicle load, service time window and the maximum travel time of the vehicle. Among the possible arrangements of all customer points, most of the corresponding ones are infeasible. When many algorithms solve the vehicle routing problem with constraints such as load or time window, they usually only keep the feasible solution and discard the infeasible solution during the solution process. But it is worth noting that among these infeasible solutions, there may be a few such infeasible solutions, that is, a feasible solution with better quality can be obtained after a ...

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Abstract

The invention provides a variable neighborhood search algorithm for solving multi depot vehicle routing problem with time windows. The variable neighborhood search algorithm is characterized in that in a local searching progress, an or-opt and 2-opt mixed operator is utilized for local searching; a Metropolis rule in a simulated annealing algorithm model is introduced into a basic frame of VNS (variable neighborhood search) algorithm for accepting partial poorer solutions under a certain condition, so that the possibility that the algorithm is trapped into local optimization is reduced; in this way, the reliability of the algorithm is improved; and a rear optimization progress is added into the algorithm framework, as a result, both the solving quality is improved and the convergence speed of the algorithm is increased in a way.

Description

technical field [0001] The invention relates to a vehicle scheduling problem in the field of operations research, and specifically relates to a variable neighborhood search algorithm for solving the multi-depot vehicle routing problem with a time window or a solution model based on a variable neighborhood search algorithm. Background technique [0002] A large number of logistics vehicle scheduling problems in reality can be attributed to the Multi Depot Vehicle Routing Problem with Time Windows (MDVRPTW): logistics vehicles are initially separated in multiple depots at different physical locations, and they need Deliver the specified quantity of goods to the customer within the required time frame with the least route cost, and finally return to the depot. [0003] Although the practical application of MDVRPTW has been very extensive, this problem has not been well resolved in theoretical research. The dual constraints imposed by "multi-depot" and "time window" respectivel...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 张俊颜秉珩
Owner LANGCHAO ELECTRONIC INFORMATION IND CO LTD
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