Jijiang Yu
Department of Computer and Information Engineering, Heze University, Heze, China
Chunying Liu
Department of Computer and Information Engineering, Heze University, Heze, China
Yuwen Huang
Department of Computer and Information Engineering, Heze University, Heze, China
ABSTRACT
In order to improve the efficiency of the multiple depots vehicle routing, Combines the advantages of immune clone algorithm with simulated annealing, brings forward a new algorithm based on simulated Annealing Immune Clone Algorithm in multiple depots vehicle routing optimization. The new algorithm provides not only with the strong global search capability of the immune clone algorithm, but also with the strong local capability of the simulated annealing algorithm. Give the multiple depots vehicle scheduling model and the coding method of the vehicle route. One the one hand, Accelerate the searching process by the tensile annealing of the affinity function. On the other hand, the new antibodies are accepted by the simulated annealing rule in the mutation and crossover and speed up the global searching ability. The optimal solution is got by simulated annealing regulation when the annealing temperature is tended to zero. The simulation results demonstrate that the solving result of the fusion algorithm is more excellent than the other algorithms and it improves the performance in searching speed and increases the global astringency compared with simple immune clone algorithm.
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How to cite this article
Jijiang Yu, Chunying Liu and Yuwen Huang, 2013. Cost-sensitive Multi-distribution Center Vehicle Routing Optimization Based on Improved Immune Clone Algorithm. Information Technology Journal, 12: 7965-7970.
DOI: 10.3923/itj.2013.7965.7970
URL: https://scialert.net/abstract/?doi=itj.2013.7965.7970
DOI: 10.3923/itj.2013.7965.7970
URL: https://scialert.net/abstract/?doi=itj.2013.7965.7970
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