Large-Scale Truss-Sizing Optimization with Enhanced Hybrid HS Algorithm

Metaheuristic algorithms currently represent the standard approach to engineering optimization. A very challenging field is large-scale structural optimization, entailing hundreds of design variables and thousands nonlinear constraints on element stresses nodal displacements. However, few studies documented use metaheuristic in In order fill this gap, an enhanced hybrid harmony search (HS) algorithm for weight minimization truss structures presented study. The new algorithm, Large-Scale Structural Optimization–Hybrid Harmony Search JAYA (LSSO-HHSJA), developed here, combines a well-established method like HS with recent JAYA, which has simplest inherently most powerful engine amongst optimizers. All stages LSSO-HHSJA are aimed at reducing number analyses required basic idea move along descent directions generate trial designs, directly through gradient information phase, indirectly by correcting designs JA-based operators that push towards best stored population or included local neighborhood analyzed design. proposed tested three problems structures. Optimization results obtained benchmark examples, up 280 sizing 37,374 constraints, prove efficiency competitive other variants as well commercial gradient-based