Performance assessment of meta-heuristics for composite layup optimisation

Abstract

AbstractThis paper investigates the performance of several meta-heuristic algorithms, including Particle Swarm Optimisation (PSO), different variants of Differential Evolution (DE), Biogeography-Based Optimisation (BBO), Cultural Algorithm (CA), Optics-Inspired Optimisation (OIO), and League Championship Algorithm (LCA), for optimum layup of laminated composite plates. The study provides detailed Pseudo codes for different algorithms. The buckling capacity maximisation of a 64-layer laminated composite plate under various load scenarios has been considered as the benchmark problem, in which the design variables are the stacking sequences of layers. A Deep Statistical Comparison (DSC) method is employed to rank the performance of different algorithms. The DSC uses a nonparametric two-sample Kolmogorov-Smirnov test to conduct the performance comparisons between the algorithms. The overall performance rankings obtained from the DSC suggest that the LCA, OIO, and PSO algorithms perform remarkably better in comparison to other algorithms. The comparisons provide some interesting conclusions on the performance of different algorithms.