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Hybrid immune algorithm based on greedy algorithm and delete-cross operator for solving TSP

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Abstract

This paper first introduces the fundamental principles of immune algorithm (IA), greedy algorithm (GA) and delete-cross operator (DO). Based on these basic algorithms, a hybrid immune algorithm (HIA) is constructed to solve the traveling salesman problem (TSP). HIA employs GA to initialize the routes of TSP and utilizes DO to delete routes of crossover. With dynamic mutation operator (DMO) adopted to improve searching precision, this proposed algorithm can increase the likelihood of global optimum after the hybridization. Experimental results demonstrate that the HIA algorithm is able to yield a better solution than that of other algorithms, which also takes less computation time.

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Acknowledgments

We are very grateful to the anonymous reviewers and the editors for their comments. The research was partially funded by the Key Program of National Natural Science Foundation of China (Grant Nos. 61133005, 61432005), and the National Natural Science Foundation of China (Grant Nos. 61370095, 61472124), the Ph.D. Programs Foundation of Ministry of Education of China (20100161110019), the Research Foundation of Education Bureau of Hunan Province (No. 13C333), the Project Supported by the Science and Technology Research Foundation of Hunan Province (Grant No. 2014GK3043).

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Authors and Affiliations

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, Hunan, China

    Guo Pan, Kenli Li, Aijia Ouyang & Keqin Li

  2. Department of Computer Science, State University of New York, New Paltz, NY, 12561, USA

    Keqin Li

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  1. Guo Pan
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  2. Kenli Li
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  3. Aijia Ouyang
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  4. Keqin Li
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Correspondence to Kenli Li.

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Communicated by V. Loia.

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Pan, G., Li, K., Ouyang, A. et al. Hybrid immune algorithm based on greedy algorithm and delete-cross operator for solving TSP. Soft Comput 20, 555–566 (2016). https://doi.org/10.1007/s00500-014-1522-3

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