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Multi-group discrete symbiotic organisms search applied in traveling salesman problems

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Abstract

Recent years have witnessed a growing development in swarm intelligence. With its distinctive advantages in settling complex issues in practice, more and more researchers have paid attention to this point. Compared with other swarm algorithms, the symbiotic organism search (SOS) algorithm, a promising meta-heuristic evolutionary one, is featured by high convergence and high-quality solutions in the overall optimization process. However, when the SOS algorithm was proposed, it was to solve real-life problems, and there are many discrete problems to be solved by us, so some scholars discretized the SOS algorithm. The discretized SOS algorithm has the shortcoming that it is very easy to fall into the local optimum, which leads to insufficient convergence, so in this paper, we propose a multi-group discrete SOS algorithm with gene transfer and path cross for elimination strategies to improve the performance of the DSOS algorithm in solving TSP. To prove the performance and efficiency of the algorithm for the TSP problem, the symmetry problem in the TSPLIB data set is employed to verify it, and this paper compares it with other algorithms to show the practicability of the method.

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Data Availability

The data sets generated during or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This research was funded by the National Natural Science Foundation of China (Grant Number NSF 215 61872085), Project 2018Y3001 of Fujian Provincial Department of Science and Technology, and Natural Science Foundation of Fujian Province (Grant Number 2018J01638).

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Authors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, Shandong, China

    Zhi-Gang Du, Jeng-Shyang Pan & Shu-Chuan Chu

  2. College of Information Science and Technology, Dalian Maritime University, Dalian, 10587, China

    Jeng-Shyang Pan

  3. College of Science and Engineering, Flinders University, 1284 South Road, Clovelly Park, SA, 5042, Australia

    Shu-Chuan Chu

  4. School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen, 361024, Fujian, China

    Yi-Jui Chiu

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  1. Zhi-Gang Du
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Correspondence to Shu-Chuan Chu.

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Du, ZG., Pan, JS., Chu, SC. et al. Multi-group discrete symbiotic organisms search applied in traveling salesman problems. Soft Comput 26, 4363–4373 (2022). https://doi.org/10.1007/s00500-022-06862-x

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