Individual Disturbance and Attraction Repulsion Strategy Enhanced Seagull Optimization for Engineering Design

Helong Yu, Shimeng Qiao, Ali Asghar Heidari, Chunguang Bi and Huiling Chen
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Helong Yu: College of Information Technology, Jilin Agricultural University, Changchun 130118, China
Shimeng Qiao: College of Information Technology, Jilin Agricultural University, Changchun 130118, China
Ali Asghar Heidari: Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China
Chunguang Bi: College of Information Technology, Jilin Agricultural University, Changchun 130118, China
Huiling Chen: Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China

Mathematics, 2022, vol. 10, issue 2, 1-35

Abstract: The seagull optimization algorithm (SOA) is a novel swarm intelligence algorithm proposed in recent years. The algorithm has some defects in the search process. To overcome the problem of poor convergence accuracy and easy to fall into local optimality of seagull optimization algorithm, this paper proposed a new variant SOA based on individual disturbance (ID) and attraction-repulsion (AR) strategy, called IDARSOA, which employed ID to enhance the ability to jump out of local optimum and adopted AR to increase the diversity of population and make the exploration of solution space more efficient. The effectiveness of the IDARSOA has been verified using representative comprehensive benchmark functions and six practical engineering optimization problems. The experimental results show that the proposed IDARSOA has the advantages of better convergence accuracy and a strong optimization ability than the original SOA.

Keywords: seagull optimization algorithm; swarm intelligence; individual disturbance; attraction-repulsion strategy; engineering design (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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