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RDEx-CMOP: Feasibility-Aware Indicator-Guided Differential Evolution for Fixed-Budget Constrained Multiobjective Optimization

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Constrained multiobjective optimisation requires fast feasibility attainment together with stable convergence and diversity preservation under strict evaluation budgets. This report documents RDEx-CMOP, the differential evolution variant used in the IEEE CEC 2025 numerical optimisation competition (C06 special session) constrained multiobjective track. RDEx-CMOP integrates an {\epsilon}-level feasibility schedule, a SPEA2-style indicator-driven fitness assignment, and a fitness-oriented current-to-pbest/1 mutation operator. We evaluate RDEx-CMOP on the official CEC 2025 CMOP benchmark using the median-target U-score framework and the released trace data. Experimental results show that RDEx-CMOP achieves the highest total score and the best overall average rank among all released comparison algorithms, with strong target-attainment behaviour and near-zero final violation on most problems.

Sichen Tao, Yifei Yang, Ruihan Zhao, Kaiyu Wang, Sicheng Liu, Shangce Gao• 2026

Related benchmarks

TaskDatasetResultRank
Constrained Multi-objective OptimizationCEC CMOP (15 problems) 2025
Speed5.29e+4
12
Constrained Multi-objective Optimization15 CEC2025 CMOP functions
Final IGD1.77
6
Constrained Multiobjective OptimizationCEC CMOP 15 Functions 2025
Final Quality (Q)1.77
6
Constrained Multi-objective OptimizationCEC CMOP 2025
Wilcoxon Win Count15
5
Constrained Multi-objective OptimizationCEC CMOP 2025
Wilcoxon Win Count13
5
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