Method and device for dynamic vehicle receipt and delivery path planning based on meme calculation

Abstract

The invention is applicable to the technical field of path planning, and provides a method and device for dynamic vehicle receipt and delivery path planning based on meme calculation. First, code initialization is performed, then path correction is performed on N chromosomes, and crossover in genetic algorithm is performed. According to the pre-established sorting library, local search optimization is carried out in a sorting-first manner; then N chromosomes are selected from the N optimized new chromosomes and the N original chromosomes as the N types of path planning to be executed. Finally, select a route planning scheme from the N route planning schemes to serve one of the service points, and after the service is completed, the service point is extracted from the N chromosomes as the service point that has been served, and It is judged whether all service points have been served, if not, return to the correction step until all service points have been served; the method provided by the present invention can shorten the distance, increase the workload, and improve the local search ability.

Description

technical field [0001] The invention belongs to the technical field of route planning, and in particular relates to a method and device for dynamic vehicle receiving and dispatching route planning based on meme calculation. Background technique [0002] Pickup-and-delivery problems (PDPs for short) is a kind of logistics vehicle routing problem (VRP for short). The volume of delivery is the largest. Solving the problem of PDPs can promote energy conservation and emission reduction, relieve traffic pressure, and make a certain contribution to the sustainable development of cities. Most of the PDPs use static models, that is, all information is known in advance and does not change. In real life, with the increasing pressure of competition and customers expecting better services, these requirements force logistics companies to reform and improve service levels. Nowadays, e-commerce at home and abroad is booming, producing a large number of packages. In addition, services suc...

AI Technical Summary

Problems solved by technology

[0006] Existing path planning algorithms often can only solve single-objective optimization and have defects such as time-consuming and easy to fall into local optimum.

Other few algorithms are mainly general-purpose heuristic algorithms, which have limited optimization for targeted problems. For example, in multi-objective problems, only the length is considered for local optimization, and even the heuristic information of the problem (such as time, point-to-point distance, etc.) is not considered. information such as distance sorting)

In addition, due to the lack of local positioning ability, the heuristic algorithm also has the defect of slow global search convergence when solving complex problems.

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