The Whale Optimization Algorithm. (May 2016)

• Record Type: Journal Article
• Authors: Mirjalili, Seyedali; Lewis, Andrew
• Is Part Of: Advances in engineering software. Volume 95(2016)
• Page Start: 51
• Page End: 67
• Publication Date: 2016-05
• Subjects: Optimization -- Benchmark -- Constrained optimization -- Particle swarm optimization -- Algorithm -- Heuristic algorithm -- Genetic algorithm -- Structural optimization; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2016.01.008
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: The Whale Optimization Algorithm inspired by humpback whales is proposed. The WOA algorithm is benchmarked on 29 well-known test functions. The results on the unimodal functions show the superior exploitation of WOA. The exploration ability of WOA is confirmed by the results on multimodal functions. The results on structural design problems confirm the performance of WOA in practice. Abstract: This paper proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales. The algorithm is inspired by the bubble-net hunting strategy. WOA is tested with 29 mathematical optimization problems and 6 structural design problems. Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods. The source codes of the WOA algorithm are publicly available athttp://www.alimirjalili.com/WOA.html