A Comparative Study of Eighteen Self-adaptive Metaheuristic Algorithms for Truss Sizing Optimisation

Abstract

Performance comparison of meta-heuristics (MHs) is conducted for truss sizing design. Six traditional truss sizing design problems with mass objective function subject to displacement and stress constraints were employed for performance test. The test problems have two types with and without including buckling constraints. Eighteen self-adaptive MHs from literature are employed to tackle the truss sizing problems. The results from implementing the self-adaptive MHs are compared in terms of convergence rate and consistency. It is found that for the test problem without buckling constraints, the top two optimisers according to the statistical Wilcoxon rank sum tests are Success-History Based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) and Success-History Based Adaptive Differential Evolution (SHADE) while the top two optimiser for the test problems with buckling constraints is L-SHADE and L-SHADE with Eigenvector-Based Crossover and Successful-Parent-Selecting Framework (SPS-L-SHADE-EIG). The buckling constraints are significantly important and should be included to truss design subjected to static loads.