A comprehensive survey: Whale Optimization Algorithm and its applications

By Farhad Soleimanian Gharehchopogh, Hojjat Gholizadeh. Swarm and Evolutionary Computation, 2019

676 citations recorded by the source corpus.

Abstract Whale Optimization Algorithm (WOA) is an optimization algorithm developed by Mirjalili and Lewis in 2016. An overview of WOA is described in this paper, rooted from the bubble-net hunting strategy, besides an overview of WOA applications that are used to solve optimization problems in various categories. The best solution has been determined to make something as functional and effective as possible through the optimization process by minimizing or maximizing the parameters involved in the problems. Research and engineering attention have been paid to Meta-heuristics for purposes of decision-making given the growing complexity of models and the needs for quick decision making in the engineering. An updated review of research of WOA is provided in this paper for hybridization, improved, and variants. The categories included in the reviews are Engineering, Clustering, Classification, Robot Path, Image Processing, Networks, Task Scheduling, and other engineering applications. According to the reviewed literature, WOA is mostly used in the engineering area to solve optimization problems. Providing an overview and summarizing the review of WOA applications are the aims of this paper.

Subfields: Artificial Intelligence, Computer Networks and Communications, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/e3b83d360bae8512fada222856f561da03097e32

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In Artificial Intelligence

Citations in the corpus

Puma optimizer (PO): a novel metaheuristic optimization algorithm and its application in machine learning (2024, neutral): “However, this method was weak in more complicated optimization problems, which could result in local optima trapping [4, 5] or various premature convergence inability for stochastic or unexplained search space problems.”
Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems (2022, background): “Further readings and details of WOA can be seen in Mirjalili and Lewis (2016); Gharehchopogh and Gholizadeh (2019); Adhirai et al. (2018); Mirjalili et al. (2020); Mohammed et al. (2019).”
Advances in Sparrow Search Algorithm: A Comprehensive Survey (2022, background): “Because the search space in actual optimization issues increases exponentially and the problem perspective shifts in a multidimensional fashion, standard optimization methods frequently generate less-than-optimal solutions [1–3].”