WASHH is an anchor-aware whale-guided selection hyper-heuristic that achieves best average rank 1.10 on ten 30D benchmarks and lowest mean validation log loss for SVC configuration under 300 evaluations.
Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces.Journal of Global Optimization, 11(4):341–359,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NE 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
WASHH: An Anchor-Aware Whale-Guided Selection Hyper-Heuristic for Continuous Optimization and SVC Configuration
WASHH is an anchor-aware whale-guided selection hyper-heuristic that achieves best average rank 1.10 on ten 30D benchmarks and lowest mean validation log loss for SVC configuration under 300 evaluations.