Abstract
Vehicle routing problems (VRP) arise in many real-life applications within transportation and logistics. This paper considers vehicle routing models with fuzzy travel times and its hybrid intelligent algorithm. Two new types of credibility programming models including fuzzy chance-constrained programming and fuzzy chance-constrained goal programming are presented to model fuzzy VRP. A hybrid intelligent algorithm based on fuzzy simulation and genetic algorithm is designed to solve the proposed fuzzy VRP models. Moreover, some numerical experiments are provided to demonstrate the applications of the models and the computational efficiency of the proposed approach.
Keywords: vehicle routing problem, fuzzy travel times, fuzzy programming, hybrid intelligent algorithm.
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© 2006 Springer-Verlag Berlin Heidelberg
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Peng, J., Shang, G., Liu, H. (2006). A Hybrid Intelligent Algorithm for Vehicle Routing Models with Fuzzy Travel Times. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence. ICIC 2006. Lecture Notes in Computer Science(), vol 4114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37275-2_122
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DOI: https://doi.org/10.1007/978-3-540-37275-2_122
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37274-5
Online ISBN: 978-3-540-37275-2
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