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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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| Publicado no: | PLoS One |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5528885/ https://ncbi.nlm.nih.gov/pubmed/28746355 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0181747 |
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