Critical Evaluation of Metaheuristic Algorithms for Weight Minimization of Truss Structures

Aristotelis E Charalampakis,George C Tsiatas

doi:10.3389/fbuil.2019.00113

Abstract

This study critically compares variants of Genetic Algorithms, Particle Swarm Optimization, Artificial Bee Colony, Differential Evolution and Simulated Annealing used in truss sizing optimization problems including displacement and stress constraints. The comparison is based on several benchmark problems of varying complexity number of design variables. i.e. the number of design variables, and the degree of static indeterminacy. Most of these problems have been studied by numerous researchers using a large variety of methods; this allows for absolute rather than relative comparison. Rigorous statistical analysis based on large sample size, as well as monitoring of the success rate throughout the optimization process, reveal and explain the convergence behavior observed for each method. The results indicate that, for the problem at hand, Differential Evolution is the best algorithm in terms of robustness, performance, and scalability.

Highlights

Structural optimization has always been a topic of interest for both the research community and the practicing engineers
In order to clearly assess the differences between algorithms, rigorous statistical analysis with large samples was used, based on common computational budget depended on the problem dimensionality, careful accounting for all function evaluations and monitoring of the success rate of each algorithm during the analyses
Standard Genetic Algorithm (SGA) provides a baseline performance while the Hybrid Genetic Algorithm (HGA), which combines a search space reduction method (SSRM) with a local optimizer, showed improved performance with respect to SGA

Summary

INTRODUCTION

Structural optimization has always been a topic of interest for both the research community and the practicing engineers. The average progress of the best design and the evolution of success rate with respect to the number of structural analyses are plotted in Figure 11 for all algorithms.

CONCLUDING REMARKS

Findings

DATA AVAILABILITY STATEMENT