Application of genetic algorithms to vehicle routing problem

Title:

Application of genetic algorithms to vehicle routing problem

Creator:

Mocková, Denisa and Rybičková , Alena

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:c297b5f9-144c-4894-9838-f614ac2fc06a
uuid:c297b5f9-144c-4894-9838-f614ac2fc06a
doi:10.14311/NNW.2014.24.003

Subject:

VRP problem, genetic algorithms, Clarke-Wright algorithm, and metaheuristic

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

Distribution of the goods from a producer to a customer is one of the most important tasks of transportation. This paper focuses on the usage of genetic algorithms (GA) for optimizing problems in transportation, namely vehicle routing problem (VRP). VRP falls in the field of NP-hard problems, which cannot be solved in polynomial time. The problem was solved using genetic algorithm with two types of crossover, both including and leaving-out elitism, setting variable parameters of crossover and mutation probability, as well as prevention of creating invalid individuals. The algorithm was programmed in Matlab, tested on real world problem of spare parts distribution for garages, while the results were compared with another heuristic method (Clarke-Wright method). Genetic algorithm provided a better solution than the heuristic Clarke-Wright method.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2014 Volume:24 | Number:1

Harvested from:

CDK

Metadata only:

false