Abstract
This research introduces a refined variant of the Aquila optimizer (AO) through a novel population segmentation technique. The new algorithm named Population Segmentation-Aquila Optimizer (PS-AO), strategically partitions search agents to achieve better exploration-exploitation trade-offs and increased solution diversity. We validate PS-AO’s effectiveness through extensive testing on IEEE CEC 2019 benchmark functions and two mechanical engineering design problems. The experimental outcomes reveal that PS-AO achieves superior performance metrics in solution accuracy.
Keywords: Optimization, Nature Inspired Metaheuristic Algorithm, Aquila Optimizer, Engineering Design Problem
How to cite
Megha Varshney, Pravesh Kumar, Pinkey Chauhan (2025). A Novel Population Segmentation-Aquila Optimizer for solving Engineering Design problems. International Journal of Mathematics and Computational Frontiers, 1(1), 65–79.