TL;DR
Experimental results show that MOAEO achieves competitive convergence and diversity across multiple benchmark suites, and highlights MOAEO’s potential as an effective approach for solving complex multi-objective optimization problems.
The proposed Multi-Objective Narwhal Optimizer (MONO), a Pareto-based extension of the recently developed Narwhal Optimizer, incorporates Pareto dominance, external archive management, adaptive multi-leader guidance, and crowding-distance-based diversity preservation to effectively balance convergence and exploration t...
This work presents an enhanced multi-objective dung beetle optimization algorithm that is implemented to tackle the multi-objective path planning optimization problem for mobile robot, and numerical simulation results verify that the method achieves sound performance in resolving practical engineering issues.
Multi-objective optimization plays an important role in modern design and complex engineering applications. However, achieving an effective balance between the convergence and diversity of Pareto-optimal solutions remains challenging. This paper proposes a Sobol-driven Multi-objective Whale Migration Algorithm (SMOWMA)...
Results show that integrating local search significantly enhances performance, while a principled method for setting hybrid parameters ensures robustness and reproducibility, highlighting the potential of combining mathematical programming techniques with evolutionary algorithms for high-dimensional many-objective opti...
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