Abstract:We extend RDEx-CSOP with 3 changes that target stagnation & late-stage variance, plus minor parameter tuning. The second scale factor in the standard branch is sampled independently from a truncated Cauchy. A small feasible-only JADE-style archive (|A|_max = 50) is added & sampled with probability |A|/(|A|+|P|). Per-individual stagnation counter triggers, after 180 no-improvement generations, three local overrides on standard branch: pull toward the global best, lift the archive sampling floor to 0.65, & saturate CR to 0.95 when population success rate is below 0.10. The exploitation biased branch & every other RDEx component are left untouched. On CEC CSOP suite (D=30, 25 runs), RDEx-CASK is competitive with RDEx, UDE-III, & CL-SRDE in feasibility-aware quality & improves time-to-target on most problems.
| Comments: | 5 pages, 2 tables, 1 algorithm. Technical report for the CEC 2026 CSOP competition track |
| Subjects: | Neural and Evolutionary Computing (cs.NE); Artificial Intelligence (cs.AI) |
| MSC classes: | 90C30, 90C59 |
| ACM classes: | I.2.8; G.1.6 |
| Cite as: | arXiv:2605.09652 [cs.NE] |
| (or arXiv:2605.09652v1 [cs.NE] for this version) | |
| https://doi.org/10.48550/arXiv.2605.09652 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Dikshant Dikshant [view email]
[v1]
Sun, 10 May 2026 16:53:41 UTC (10 KB)