# RDEx-CSOP: Feasibility-Aware Reconstructed Differential Evolution with Adaptive epsilon-Constraint Ranking

arXiv: https://arxiv.org/abs/2603.27090 · HTML: https://mlsanity.com/paper/2603.27090/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 14 references that are in the map.
- First posted on arXiv 28 Mar 2026.

## Builds on (most cited first, 2 of 2)

- [Reviewing and Benchmarking Parameter Control Methods in Differential Evolution](https://mlsanity.com/paper/2010.01035/) (2020)
- [An Improved LSHADE-RSP Algorithm with the Cauchy Perturbation: iLSHADE-RSP](https://mlsanity.com/paper/2006.02591/) (2020)

## Built on by (most cited first, 1 of 1)

- [RDEx-CASK: Cauchy Mutation, Archive, and Stagnation Kick for RDEx-CSOP](https://mlsanity.com/paper/2605.09652/) (2026)

## Abstract (arXiv)

Constrained single-objective numerical optimisation requires both feasibility maintenance and strong objective-value convergence under limited evaluation budgets. This report documents RDEx-CSOP, a constrained differential evolution variant used in the IEEE CEC 2025 numerical optimisation competition (C06 special session). RDEx-CSOP combines success-history parameter adaptation with an exploitation-biased hybrid search and an ε-constraint handling mechanism with a time-varying threshold. We evaluate RDEx-CSOP on the official CEC 2025 CSOP benchmark using the U-score framework (Speed, Accuracy, and Constraint categories). The results show that RDEx-CSOP achieves the highest total score and the best average rank among all released comparison algorithms, mainly through strong speed and competitive constraint-handling performance across the 28 benchmark functions.