CLTSA: A Novel Tunicate Swarm Algorithm Based on Chaotic-Lévy Flight Strategy for Solving Optimization Problems

Yi Cui, Ronghua Shi and Jian Dong
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Yi Cui: School of Computer Science and Engineering, Central South University, Changsha 410083, China
Ronghua Shi: School of Computer Science and Engineering, Central South University, Changsha 410083, China
Jian Dong: School of Computer Science and Engineering, Central South University, Changsha 410083, China

Mathematics, 2022, vol. 10, issue 18, 1-39

Abstract: In this paper, we proposed a tunicate swarm algorithm based on Tent-Lévy flight (TLTSA) to avoid converging prematurely or failing to escape from a local optimal solution. First, we combined nine chaotic maps with the Lévy flight strategy to obtain nine different TSAs based on a Chaotic-Lévy flight strategy (CLTSA). Experimental results demonstrated that a TSA based on Tent-Lévy flight (TLTSA) performed the best among nine CLTSAs. Afterwards, the TLTSA was selected for comparative research with other well-known meta-heuristic algorithms. The 16 unimodal benchmark functions, 14 multimodal benchmark functions, 6 fixed-dimension functions, and 3 constrained practical problems in engineering were selected to verify the performance of TLTSA. The results of the test functions suggested that the TLTSA was better than the TSA and other algorithms in searching for global optimal solutions because of its excellent exploration and exploitation capabilities. Finally, the engineering experiments also demonstrated that a TLTSA solved constrained practical engineering problems more effectively.

Keywords: tunicate swarm algorithm; chaotic mapping; Lévy flight strategy; benchmark test functions; engineering design problems; meta-heuristic (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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