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Multi-objective Differential Evolution Algorithm Integrating a Directional Generation Mechanism for Multi-objective Optimization Problems

delete2025-08-23
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PRE
AI
Z
Zhuoxuan Yuan
H
Haibin Ouyang *
S
Steven Li
E
Essam H. Houssein
N
Nagwan Abdel Samee
DOI:10.1016/j.asoc.2025.113791delete
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Abstract

Abstract

En 中文
• 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

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
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1.4W
Citations:
4.8W

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M
minia university
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Princess Nourah bint Abdulrahman University
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Guangzhou University
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RMIT University
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