The Crossover strategy integrated Secretary Bird Optimization Algorithm and its application in engineering design problems

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Abstract

An improved metaheuristic algorithm called the Crossover strategy integrated Secretary Bird Optimization Algorithm (CSBOA) is proposed in this work for solving real optimization problems. This improved algorithm integrated logistic-tent chaotic mapping initialization, an improved differential mutation operator, and crossover strategies with the Secretary Bird Optimization Algorithm (SBOA) for a better quality solution and faster convergence. To evaluate the performance of CSBOA, two sets of a standard benchmark set, CEC2017 and CEC2022, were applied first. The Wilcoxon rank sum test and Friedman test were also used to statistically compare the proposed CSBOA algorithm with seven common metaheuristics. The comparisons demonstrated that CSBOA is more competitive than other metaheuristic algorithms on most benchmark functions. Additionally, the performance of CSBOA was validated for two challenging engineering design case studies. Comparative results showed that CSBOA provides more accurate solutions than the SBOA and the other seven algorithms, suggesting viability in dealing with real global optimization problems.

Keywords

Secretary Bird Optimization Algorithm / logistic-tent chaotic mapping / improved differential mutation operator / crossover strategies / engineering design problems

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