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...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2017-01-01
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Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5528885?pdf=render |