Abstract
Tailored to the individual demands and the diversified requirements in the real operation, this paper is focused on the min-max vehicle routing problem (MMVRP) to shorten the longest journey in the circuit. New genetic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; apply insertion method so as to improve the feasibility of the solution. Secondly, use the individual amount control choice strategy so as to guard the diversity of group; apply improved route crossover operation to avoid destroying good gene parts. Finally, the good performance of improved algorithm can be proved by experiment calculation and concrete examples.
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© 2012 Springer-Verlag Berlin Heidelberg
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Ren, C. (2012). New Genetic Algorithm for Min-Max Vehicle Routing Problem. In: Qu, X., Yang, Y. (eds) Information and Business Intelligence. IBI 2011. Communications in Computer and Information Science, vol 268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29087-9_4
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DOI: https://doi.org/10.1007/978-3-642-29087-9_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29086-2
Online ISBN: 978-3-642-29087-9
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