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A Hybrid Intelligent Algorithm for Vehicle Routing Models with Fuzzy Travel Times

  • Jin Peng
  • Gang Shang
  • Huanbin Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

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.

Keywords

Fuzzy Variable Vehicle Rout Problem Stochastic Demand Capacitate Vehicle Route Problem Fuzzy Simulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jin Peng
    • 1
  • Gang Shang
    • 1
  • Huanbin Liu
    • 1
  1. 1.College of Mathematics and Information Sciences, Huanggang Normal University, Hubei 438000China

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