Threshold-Based Selection for Continuous Optimization: A Leaf-Abscission Instantiation

• URL: http://arxiv.org/abs/2609.10588v1
• Date: Sun, 06 Sep 2026 17:41:35 GMT
• Title: Threshold-Based Selection for Continuous Optimization: A Leaf-Abscission Instantiation
• Abstract summary: Leaf Abscission Optimization (LAO) uses rank-based strength, a phenological seasonal signal, diversity modulation, environmental pressure, and a base regrowth kernel.<n>This paper formalizes threshold-based selection as an evaluation-gating architecture in which each incumbent is tested before variation and a replacement is generated and evaluated only when contextual pressure exceeds strength.
• Score: 1.827510863075184
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper formalizes threshold-based selection as an evaluation-gating architecture in which each incumbent is tested before variation and a replacement is generated and evaluated only when contextual pressure exceeds intrinsic strength. The mechanism is instantiated as Leaf Abscission Optimization (LAO), using rank-based strength, a phenological seasonal signal, diversity modulation, environmental pressure, and a base regrowth kernel. A blocked two-to-the-fourth-power factorial analysis at dimension 10 on the CEC 2017 suite reduces the original multi-layer design to a parsimonious core: drift is harmful, while the other three auxiliary layers show no robust independent evidence of benefit. The resulting LAO-Core attains the third-best mean Friedman rank among nine optimizers at dimensions 10, 30, and 50 under the equal evaluation budget. A four-budget sweep shows budget-dependent relative performance, with adaptive differential-evolution baselines gaining relative advantage at larger budgets; the nine-cell dimension-budget analysis establishes neither an evaluation-budget-per-dimension-only law nor a statistically significant dimension-budget interaction. A paired intervention shows that diversity modulation changes late-run replacement behaviour without a detectable effect on final error at the tested budget. The evidence supports LAO as a parsimonious evaluation-gating mechanism with regime-qualified competitiveness, rather than as a generally superior optimizer.

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