# RDEx-SOP: Exploitation-Biased Reconstructed Differential Evolution for Fixed-Budget Bound-Constrained Single-Objective Optimization

arXiv: https://arxiv.org/abs/2603.27089 · HTML: https://mlsanity.com/paper/2603.27089/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 13 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)

## Abstract (arXiv)

Bound-constrained single-objective numerical optimisation remains a key benchmark for assessing the robustness and efficiency of evolutionary algorithms. This report documents RDEx-SOP, an exploitation-biased success-history differential evolution variant used in the IEEE CEC 2025 numerical optimisation competition (C06 special session). RDEx-SOP combines success-history parameter adaptation, an exploitation-biased hybrid branch, and lightweight local perturbations to balance fast convergence and final solution quality under a strict evaluation budget. We evaluate RDEx-SOP on the official CEC 2025 SOP benchmark with the U-score framework (Speed and Accuracy categories). Experimental results show that RDEx-SOP achieves strong overall performance and statistically competitive final outcomes across the 29 benchmark functions.