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Data · dataset · 2026

Multi-objective archived-based whale optimization algorithm

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In this chapter, the Multi-Objective Archived-based Whale Optimization Algorithm (MAWOA) is a multi-objective version of the proposed WOA.

Description

It mimics the social behavior of humpback whales, and the algorithm is based on the bubble-net hunting strategy. The WOA algorithm incorporates three mechanisms, namely archive, grid, and leader selection, to facilitate multi-objective optimization.

As a result of this research, the MAWOA has been developed to address multi-objective optimization issues that arise in various engineering problems. Eight engineering multi-objective optimization design problems are used to evaluate MAWOA. The algorithm's effectiveness is measured concerning multiple criteria, including coverage, generational distance, spacing, and others.

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The optimization results show that the MAWOA algorithm can compete favorably with the most advanced meta-heuristic algorithms.<p></p>

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