Multi-target urban logistics distribution path planning method

Abstract

The invention discloses a multi-target urban logistics distribution path planning method. The method comprises the following steps: decomposing a three-target vehicle path problem with a time window into a plurality of single-target sub-problems through a group of uniformly distributed weight vectors; initializing the sub-problems by adopting a heuristic strategy; generating a filial generation for the sub-problem by using an evolutionary operator, and designing a target-oriented neighborhood operator to be combined with a variable neighborhood descent algorithm to serve as a local search strategy so as to improve the solving quality of the sub-problem; updating the solution of the sub-problem by adopting a Chebyshev aggregation function; optimizing a non-dominated solution in the archivesby adopting an external archive strategy based on a sorting and congestion degree mechanism; and S3, repeating the steps S3 to S4 until the set maximum number of iterations is reached, and providinga group of feasible vehicle distribution schemes for multi-target urban logistics distribution. Compared with single-target optimization, the method can provide richer decision information for a decision maker, and considers the quality of the solution on the premise of ensuring the convergence and diversity of the algorithm.

Description

technical field [0001] The invention belongs to the field of logistics dispatching, and in particular relates to a multi-objective urban logistics distribution path planning method. Background technique [0002] Vehicle Routing Problem With Time Window (VRPTW) is a typical logistics distribution problem considering customer satisfaction. The main purpose of VRPTW is to plan the driving path for a group of vehicles so that the cost is optimal under the premise of satisfying the constraints. There are many factors involved in the cost, and the driving distance and the number of vehicles are the most considered optimization goals. According to the characteristics and constraints of VRPTW, usually the optimization of one objective will lead to the deterioration of another objective, therefore, VRPTW is essentially a multi-objective optimization problem (Y.Zhou and J.Wang, “Alocal search-based multiobjective optimization algorithm for multiobjectivevehicle routing problem with ...

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Problems solved by technology

[0005] Second, from the perspective of mathematical optimization models, most of the current optimization objectives of urban distribution mathematical models only consider the two objectives of vehicle number and vehicle driving distance (B.Y.Qu, Y.S.Zhu, Y.C.Jiao, M.Y.Wu, P.N.Suganthan, and J.J. Liang, "A survey on multi-objective evolutionary algorithms for the solution of the environmental / economic dispatch problems," Swarm Evol. Comput., vol.38, no.1, pp.1–11, 2018.)

At the same time, the difficulty and high cost of parking in metropolitan cities makes early arrival an extra cost

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