Enriched Coati Osprey Algorithm: A Swarmbased Metaheuristic and Its Sensitivity Evaluation of Its Strategy

• Published in: IAENG international journal of applied mathematics Vol. 54; no. 2; pp. 277 - 285
• Main Authors: Kusuma, Purba Daru, Hasibuan, Faisal Candrasyah
• Format: Journal Article
• Language: English
• Published: Hong Kong International Association of Engineers 01.02.2024
• Subjects: Algorithms; Heuristic methods; Neighborhoods; Optimization; Optimization algorithms; Searching
• ISSN: 1992-9978

Abstract-A new swarm-based metaheuristic, namely the enriched coati osprey algorithm (ECOA), is proposed in this paper. As its name suggests, ECOA hybridizes two new metaheuristics, the coati optimization algorithm (COA) and the osprey optimization algorithm (OOA). ECOA is constructed by five searches performed sequentially by the swarm members. The first three are directed searches, while the last two are neighborhood searches. All three directed searches are adopted from COA and OOA. Meanwhile, the four-bordered neighborhood search is developed based on a new approach. During the assessment, ECOA was challenged to overcome the set of 23 functions and contended with five new metaheuristics: total interaction algorithm (TIA), golden search optimization (GSO), average and subtraction-based optimization (ASBO), COA, and OOA. The result shows that ECOA outperforms TIA, GSO, ASBO, COA, and OOA in 16,23,18,21, and 21 functions. Meanwhile, the individual search test result shows that the directed searches perform better than the neighborhood searches. Moreover, the directed search toward the best member becomes the most dominant search.