Solving traveling salesman problem using hybridization of rider optimization and spotted hyena optimization algorithm
作者：
Highlights：
• Proposed a hybrid algorithm as S-ROA for solving TSP robustly and effectively.
• Integration of ROA and SHO accomplished to resolve TSP optimally.
• Explorative and exploitative ability of S-ROA found to be remarkably superior.
• Performance of S-ROA is verified over benchmark TSP instances.
• Competence of S-ROA was proven over contemporary metaheuristic algorithms.
摘要
•Proposed a hybrid algorithm as S-ROA for solving TSP robustly and effectively.•Integration of ROA and SHO accomplished to resolve TSP optimally.•Explorative and exploitative ability of S-ROA found to be remarkably superior.•Performance of S-ROA is verified over benchmark TSP instances.•Competence of S-ROA was proven over contemporary metaheuristic algorithms.
论文关键词：TSP,Benchmark datasets,Metaheuristic algorithms,Rider-based SHO
论文评审过程：Received 18 May 2020, Revised 25 April 2021, Accepted 3 June 2021, Available online 8 June 2021, Version of Record 12 June 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115353
