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Immune clonal selection algorithm for capacitated arc routing problem

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Abstract

In existing metaheuristics for solving the capacitated arc routing problem, traversal local search operators are often used to explore neighbors of the current solutions. This mechanism is beneficial for finding high-quality solutions; however, it entails a large number of function evaluations, causing high computational complexity. Hence, there is a need to further enhance the efficiency of such algorithms. This paper proposes a high-efficiency immune clonal selection algorithm for capacitated arc routing instances within a limited number of function evaluations. First, an improved constructive heuristic is used to initialize the antibody population. The initial antibodies generated by this heuristic help accelerate the algorithm’s convergence. Second, we show how an immune clonal selection algorithm can select in favor of these high-quality antibodies. By adopting a variety of different strategies for different clones of the same antibody, it not only promotes cooperation and information exchanging among antibodies, but also increases diversity and speeds up convergence. Third, two different antibody repair operations are proposed for repairing various kinds of infeasible solutions. These operations cause infeasible solutions to move towards global optima. Experimental studies demonstrate improved performance over state-of-art algorithms, especially on medium-scale instances.

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Acknowledgments

We would like to express our sincere appreciation to Professor Xin Yao and the anonymous reviewers for their valuable comments, which have greatly helped us in improving the quality of the paper. This work was partially supported by the National Basic Research Program (973 Program) of China under Grant 2013CB329402, the National Natural Science Foundation of China, under Grants 61371201, 61203303 and 61272279, the Program for Cheung Kong Scholars and Innovative Research Team in University under Grant IRT1170, and the EU FP7 project (Grant no. 247619) on “NICaiA: Nature Inspired Computation and its Applications”.

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Authors and Affiliations

  1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an, 710071, China

    Ronghua Shang, Hongna Ma, Jia Wang & Licheng Jiao

  2. Xi’an Institute of Huawei Technology Co. Ltd., Xi’an, 710075, China

    Jia Wang

  3. School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

    Rustam Stolkin

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  1. Ronghua Shang
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  2. Hongna Ma
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  3. Jia Wang
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  4. Licheng Jiao
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  5. Rustam Stolkin
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Corresponding author

Correspondence to Ronghua Shang.

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Communicated by V. Loia.

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Shang, R., Ma, H., Wang, J. et al. Immune clonal selection algorithm for capacitated arc routing problem. Soft Comput 20, 2177–2204 (2016). https://doi.org/10.1007/s00500-015-1634-4

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