RDEx-CMOP: Feasibility-Aware Indicator-Guided Differential Evolution for Fixed-Budget Constrained Multiobjective Optimization
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Constrained Multi-objective Optimization | CEC CMOP (15 problems) 2025 | Speed5.29e+4 | 12 | |
| Constrained Multi-objective Optimization | 15 CEC2025 CMOP functions | Final IGD1.77 | 6 | |
| Constrained Multiobjective Optimization | CEC CMOP 15 Functions 2025 | Final Quality (Q)1.77 | 6 | |
| Constrained Multi-objective Optimization | CEC CMOP 2025 | Wilcoxon Win Count15 | 5 | |
| Constrained Multi-objective Optimization | CEC CMOP 2025 | Wilcoxon Win Count13 | 5 |