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. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Peng, J., Shang, G., & Liu, H. (2006). A hybrid intelligent algorithm for vehicle routing models with fuzzy travel times. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4114 LNAI-II, pp. 965–976). Springer Verlag. https://doi.org/10.1007/978-3-540-37275-2_122
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