Large-Scale Truss Topology and Sizing Optimization by an Improved Genetic Algorithm with Multipoint Approximation

Tianshan Dong,Zihan Yang,Hai Huang,Chao Han,Ziqi Dai,Shenyan Chen

doi:10.3390/app12010407

Abstract

Truss size and topology optimization problems have recently been solved mainly by many different metaheuristic methods, and these methods usually require a large number of structural analyses due to their mechanism of population evolution. A branched multipoint approximation technique has been introduced to decrease the number of structural analyses by establishing approximate functions instead of the structural analyses in Genetic Algorithm (GA) when GA addresses continuous size variables and discrete topology variables. For large-scale trusses with a large number of design variables, an enormous change in topology variables in the GA causes a loss of approximation accuracy and then makes optimization convergence difficult. In this paper, a technique named the label–clip–splice method is proposed to improve the above hybrid method in regard to the above problem. It reduces the current search domain of GA gradually by clipping and splicing the labeled variables from chromosomes and optimizes the mixed-variables model efficiently with an approximation technique for large-scale trusses. Structural analysis of the proposed method is extremely reduced compared with these single metaheuristic methods. Numerical examples are presented to verify the efficacy and advantages of the proposed technique.

Highlights

Planar trusses are one of the most commonly used structural forms [1,2]
This paper proposes a new label–clip–splice strategy to improve Genetic Algorithm (GA) with a multipoint approximation method to realize simultaneous size and topology optimization for largescale trusses efficiently
A mathematical model with continuous size design variables and discrete topology design variables is established based on the ground structure

Summary

Introduction

Planar trusses are one of the most commonly used structural forms [1,2]. One of the classical problems in their design and optimization is finding the optimal topology configuration as well as the optimal size. Two main techniques are generally used to address this problem: continuum topology optimization and the discrete ground structure method. The discrete model is closer to the actual structure and does not require any postprocessing work for the terminal truss structure [11]. A large number of design variables, large search space, and a large number of design constraints are the major preventive factors in determining optimal design in a reasonable time for large-scale trusses. These are prominent differences from small ones

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Discussion

Conclusion