Deficiencies of the whale optimization algorithm and its validation method

In the context of urgent requirements for efficient metaheuristics, the whale optimization algorithm (WOA) is tailored for tackling sophisticated optimization problems and has gained extensive momentum since its emergence. By drawing inspiration from the living habits of whales involving bubble-net...

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Bibliographic Details
Published in:Expert systems with applications Vol. 237; p. 121544
Main Authors: Deng, Lingyun, Liu, Sanyang
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.03.2024
Subjects:
Benchmark
Center-bias operator
Design flaw
Useful validation method
Whale optimization algorithm
Benchmark
Design flaw
Whale optimization algorithm
Useful validation method
Center-bias operator
ISSN:0957-4174, 1873-6793
Online Access:Get full text
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Summary:In the context of urgent requirements for efficient metaheuristics, the whale optimization algorithm (WOA) is tailored for tackling sophisticated optimization problems and has gained extensive momentum since its emergence. By drawing inspiration from the living habits of whales involving bubble-net attacking, encircling prey and discovering prey, WOA seems powerful to handle challenging problems owing to its unique mechanism. Nevertheless, in this work, through comparative experiments on several standard benchmarks and their shifted versions, we discuss the design flaws of WOA and exhibit the related cause analysis. Furthermore, we employ a useful validation method to test the deficiencies of WOA. Simulation outcomes suggest that WOA integrates a center-bias operator, which makes the algorithm shift-variant and limits its performances to tackle shifted benchmarks. •Defects of the whale optimization algorithm (WOA) are analyzed.•WOA integrates a center-bias operator.•WOA performs poorly when tackling shifted benchmarks.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2023.121544