Dynamic vehicle pickup-and-delivery route planning method and device based on meme calculation

Abstract

The invention is applicable to the technical field of route planning, and provides a dynamic vehicle pickup-and-delivery route planning method and device based on meme calculation. The method comprises the steps of firstly performing code initialization, then performing route correction on N chromosomes, carrying out crossover and mutation operations in a genetic algorithm, and performing local search optimization according to a mode of the sorting priority on the basis of a pre-established sorting library; then screening out N chromosomes from the N new optimized chromosomes and the N original chromosomes to serve as N route planning schemes to be executed; selecting one route planning scheme from the N route planning schemes to serve one of the service points, extracting the service point from the N chromosomes after the service to serve as a served service point, judging whether all service points are served or not, and if not, returning the correction step until all of the servicepoints are served. The method provided by the invention can shorten the distance and improve the working capacity, and improves 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 delivery route planning based on memetic 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 such as takeaway ...

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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