Multi-AGV path planning with double-path constraints by using an improved genetic algorithm

This paper investigates an improved genetic algorithm on multiple automated guided vehicle (multi-AGV) path planning. The innovations embody in two aspects. First, three-exchange crossover heuristic operators are used to produce more optimal offsprings for getting more information than with the trad...

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Detalles Bibliográficos
Autores principales: Han, Zengliang, Wang, Dongqing, Liu, Feng, Zhao, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5528885/
https://www.ncbi.nlm.nih.gov/pubmed/28746355
http://dx.doi.org/10.1371/journal.pone.0181747

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5528885/
https://www.ncbi.nlm.nih.gov/pubmed/28746355
http://dx.doi.org/10.1371/journal.pone.0181747

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