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Walrus Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm
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OA
AI
DOI：10.21203/rs.3.rs-2174098/v1.png)
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Abstract
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Abstract
In this paper, a new bio-Inspired metaheuristic algorithm called Walrus Optimization Algorithm (WaOA) mimics walrus behaviors in nature. The fundamental inspirations employed in WaOA design are the process of feeding, migrating, escaping, and fighting predators. The WaOA implementation steps are mathematically modeled in three different phases exploration, migration, and exploitation. Sixty-eight standard benchmark functions have been employed to evaluate WaOA performance in optimization applications. The ability of WaOA to provide solutions to optimization problems has been compared with the results of ten well-known metaheuristic algorithms. The simulation results show that WaOA, with its high capability in balancing exploration and exploitation, offers superior performance and is far more competitive than the ten compared algorithms. In addition, the use of WaOA in addressing four design engineering issues demonstrates the apparent effectiveness of WaOA in real-world applications.
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