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Multi-objective Differential Evolution Algorithm Integrating a Directional Generation Mechanism for Multi-objective Optimization Problems
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DOI：10.1016/j.asoc.2025.113791.png)
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Abstract
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• We propose a novel multi-objective differential evolution algorithm, MODE-FDGM, which integrates a directional generation mechanism. The key contributions are: • A new feasible solution construction method based on the directional generation mechanism that drives the algorithm toward the non-dominated, superior solution space, improving its exploration of Pareto non-dominated solutions; • An update mechanism that combines crowding distance evaluation, iterating the population and incorporating historical information to enhance diversity and improve the ability to escape local optima; • The introduction of an ecological niche radius concept along with a dual-mutation ecological niche selection evolution strategy, which improves exploration of unexplored spaces and preserves population diversity.
Keywords:
multi-objective optimization
differential evolution
directional generation mechanism
crowding distance
ecological niche strategy
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6.6
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1.4W
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4.8W
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