Application of constriction coefficient-based particle swarm optimisation and gravitational search algorithm for solving practical engineering design problems
Sajad Ahmad Rather, P. Shanthi Bala
Abstract
The constriction coefficient-based particle swarm optimisation and gravitational search algorithm (CPSOGSA) is a heuristic optimisation technique. It uses the diversification capability of the GSA and the convergence power of CPSO. In this paper, the hybrid CPSOGSA is applied to three constrained engineering design problems, namely welded beam design (WBD), compression spring design (CSD), and pressure vessel design (PVD), to find the optimal value of the engineering objective function and design variables. The investigation of experimental outcomes has been performed through various performance metrics like statistical measures, run time analysis, convergence rate, and box plots. Moreover, statistical verification of experimental results is carried out using a signed Wilcoxon rank-sum test. Furthermore, seven heuristic algorithms were employed for comparative analysis. The simulation results clearly indicate that CPSOGSA provides better outcomes for all the three engineering benchmarks than classical PSO, standard GSA, and most of the competing algorithms.