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A competition-driven two-phase evolutionary algorithm for constrained multi-objective optimization

delete2026-02-12
delete0
PRE
AI
S
Shengwei Wang *
M
M. M. H. Yu
C
Chenhao Yuan
K
Keda Chen
A
Aobo Guo
H
Hui Duan
DOI：10.1016/j.swevo.2026.102322delete
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Abstract

Abstract

En 中文
• A competition-driven two-stage evolutionary algorithm (AAPEA) for constrained multi-objective optimization. • Dual-population co-evolution enhances diversity and search guidance. • Adaptive size adjustment reduces auxiliary population cost. • CSO based competitive search operators promote convergence to high-quality solutions.
Keywords:
constrained multi-objective optimization
two-stage evolutionary algorithm
dual-population co-evolution
adaptive size adjustment
competitive search operators

Journal

Swarm and Evolutionary Computation cover
Swarm and Evolutionary Computation
IF:
8.5
Papers:
2.1K
Citations:
1.0W

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No organization information available