FA-AQLCA: A Feasibility-Aware Adaptive Quasi-League Championship Algorithm for Structural Beam Optimization and Benchmark Evaluation

OpenAlex · İngilizce

Metaheuristic optimization algorithms are widely used in constrained engineering design problems; however, their practical performance often depends not only on objective-function minimization but also on stable convergence and reliable constraint handling. This study proposes a feasibility-aware adaptive quasi-League Championship Algorithm, termed FA-AQLCA, for structural optimization. The proposed framework integrates three complementary mechanisms: randomly shifted Halton low-discrepancy initialization, adaptive search-control parameters, and a geometry- and area-aware repair strategy combined with stress-penalty evaluation. The method was assessed using three constrained beam-design problems, namely I-beam, T-beam, and box-beam vertical-deflection minimization. A component-level ablation study was conducted using LCA, QLCA, A-LCA, AQLCA, and FA-AQLCA over 30 paired independent runs. Compared with the original LCA, FA-AQLCA reduced the mean objective value by 1.676%, 1.066%, and 1.298% for the I-beam, T-beam, and box-beam problems, respectively. It also reduced run-to-run standard deviation by approximately 99.90%, 63.74%, and 99.90%, respectively. Candidate-level feasibility increased from 50.24–68.86% before repair to 97.13–99.20% after repair, demonstrating the effectiveness of the proposed feasibility-management mechanism. Friedman and Holm-corrected Wilcoxon analyses confirmed statistically significant improvements over LCA in all three structural cases. FA-AQLCA was further compared with GA, PSO, GWO, WOA, CMA-ES, SOO, CHOA, DOA, and OOA under the same evaluation budget and constraint-handling protocol. The external comparisons showed that FA-AQLCA remained competitive with strong mainstream and recent optimizers, although it did not universally outperform all of them. Sensitivity and engineering-parameter uncertainty analyses further confirmed stable feasibility preservation under moderate parameter changes and physically meaningful perturbations in load and elastic modulus.