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In this paper, an ensemble metaheuristic algorithm (denoted as LX-BBSCA) isintroduced. It combines the strengths of Laplacian Biogeography-BasedOptimization (LX-BBO) and the Sine Cosine Algorithm (SCA) to address structuralengineering design optimization problems. Our primary objective is to mitigatethe risk of getting stuck in local minima and accelerate the algorithm'sconvergence rate. We evaluate the proposed LX-BBSCA algorithm on a set of 23benchmark functions, including both unimodal and multimodal problems of varyingcomplexity and dimensions. Additionally, we apply LX-BBSCA to tackle fivereal-world structural engineering design problems, comparing the results withthose obtained using other metaheuristics in terms of objective function valuesand convergence behavior. To ensure the statistical validity of our findings,we employ rigorous tests such as the t-test and the Wilcoxon rank test. Theexperimental outcomes consistently demonstrate that the ensemble LX-BBSCAalgorithm outperforms not only the basic versions of BBO, SCA, and LX-BBO butalso other state-of-the-art metaheuristic algorithms.

Ensemble Laplacian Biogeography-Based Sine Cosine Algorithm for Structural Engineering Design Optimization Problems