Title: Model and algorithms for dynamic and stochastic vehicle routing problem

Authors: Jingling Zhang; Wanliang Wang; Yanwei Zhao

Addresses: Key Laboratory of Special Equipment and Advanced Processing Technology Ministry of Education, Zhejiang University of Technology, Zhejiang, Hangzhou 310012, China ' College of Computer Science and Technology, Zhejiang University of Technology, Zhejiang, Hangzhou 310012, China ' Key Laboratory of Special Equipment and Advanced Processing Technology Ministry of Education, Zhejiang University of Technology, Zhejiang, Hangzhou 310012, China

Abstract: This paper researched a dynamic vehicle routing problem of stochastic requests, in which at the scheduling moment t whether customers need service can be identified, but the demand is a random variable and submits to Poisson distribution. Based on model of M.H Lars, considering the multi-depot and open characteristics, two-stage stochastic programming models with resource are established. Then an adaptive immune quantum-inspired evolutionary algorithm (AIQEA) for this dynamic problem was proposed. In the AIQEA, in order to avoid the search process into the local minimum value an immune operator is introduced to optimise sub-routes. Finally, simulation examples are tested, and analyse the optimisation results of different values of the parameters λ, experiment results show that this method can effectively solve the dynamic vehicle routing problem of stochastic requests.

Keywords: dynamic vehicle routing; vehicle routing problem; stochastic requests; recourse; two-phase stochastic programming modelling; adaptive immune quantum-inspired evolutionary algorithm; AIQEA; simulation.

DOI: 10.1504/IJMIC.2013.053542

International Journal of Modelling, Identification and Control, 2013 Vol.18 No.4, pp.364 - 371

Published online: 29 Apr 2013 *

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