A Multi-Strategy Seeker Optimization Algorithm for Optimization Constrained Engineering Problems

Abstract

This paper proposes a multi-strategy seeker optimization algorithm (MSSOA) for optimization constrained engineering problems. In this paper, three strategies were adopted to improve the poor searching capability of the seeker optimization algorithm (SOA). The first strategy was triple black hole system capture to solve the local optima issue. The second and third strategies were the multi-dimensional random interference and the precocious interference to balance the exploration and exploitation processes. These three strategies are proposed to improve respectively the SOA algorithm, and compared with the three strategies to improve together the SOA algorithm for optimizing 15 benchmark functions; the way these three strategies work together is called multi-strategy; and the efficiency of the multi-strategy is illustrated the numerical optimizing results and the convergence curves, population’s positions with iterations and the search history of the benchmark functions. The proposed multi-strategy method achieved better performance in optimizing of the benchmark functions compared to other six optimization methods. The numerical and experimental results analysis were observed with respect to the optimal solution curve, the convergence curve of the fitness function, the ANOVA tests, the calculation complexity of the algorithm, the running time of the algorithm routine, the exploration and exploitation capability, the Wilcoxon’s rank-sum test, the performance profile of algorithm. The results showed that the proposed multi-strategy method was efficient in the benchmark functions. The proposed multi-strategy method also achieved better performance in optimizing of the engineering problems and provided better solutions compared to other six optimization methods.