2026-10-07T22:27:36Z https://api.figshare.com/v2/oai

oai:figshare.com:article/31063639 2026-09-29T00:09:03Z category_28855 portal_438 item_type_14 month_year_09_2026

Multi-objective archived-based whale optimization algorithm Seyedali Mirjalili (7358132) Seyedehzahra Mirjalili (19693435) Satisfiability and optimisation Multi-objective archived-based whale optimization algorithm Real-world engineering problems Whale optimization algorithm In this chapter, the Multi-Objective Archived-based Whale Optimization Algorithm (MAWOA) is a multi-objective version of the proposed WOA. 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. The optimization results show that the MAWOA algorithm can compete favorably with the most advanced meta-heuristic algorithms.<p></p> 2026-09-29T00:09:03Z Text Conference contribution 10.1016/B978-0-32-395365-8.00019-1 https://figshare.com/articles/conference_contribution/Multi-objective_archived-based_whale_optimization_algorithm/31063639 CC BY 4.0