Hybrid Scatter Search with Extremal Optimization for Solving the Capacitated Vehicle Routing Problem

Authors:
Kai Sun;Gen-Ke Yang;Yu-Wang Chen
Affiliations:
Department of Automation, Shanghai Jiaotong University, Shanghai, China. P.R.;Department of Automation, Shanghai Jiaotong University, Shanghai, China. P.R.;Department of Automation, Shanghai Jiaotong University, Shanghai, China. P.R.
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

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Abstract

Capacitated vehicle routing problem (CVRP) is one of the most well-known and well-studied scheduling problems in operation research and logistics. However, it is quite difficult to achieve an optimal solution with the traditional optimization methods owing to the high computational complexity. The paper focuses on developing a hybrid optimization algorithm by incorporating the extremal optimization into a scatter search conceptual framework to solve the CVRP. The proposed algorithm is applied to a set of benchmark problems and the performance of the algorithm is evaluated by comparing the obtained results with the results published in the literature. Comparing results indicate that this new method is an effective and competitive approach for the capacitated vehicle routing problem.