Elite-initial population for efficient topology optimization using multi-objective genetic algorithms
Hyunjin Shin, Akira Todoroki / Yoshiyasu Hirano
International Journal of Aeronautical and Space Sicences, vol. 14, no. 4, pp.324-333, 2013
Abstract : The purpose of this paper is to improve the efficiency of multi-objective topology optimization using a genetic algorithm
(GA) with bar-system representation. We proposed a new GA using an elite initial population obtained from a Solid Isotropic
Material with Penalization (SIMP) using a weighted sum method. SIMP with a weighted sum method is one of the most
established methods using sensitivity analysis. Although the implementation of the SIMP method is straightforward and
computationally effective, it may be difficult to find a complete Pareto-optimal set in a multi-objective optimization problem.
In this study, to build a more convergent and diverse global Pareto-optimal set and reduce the GA computational cost, some
individuals, with similar topology to the local optimum solution obtained from the SIMP using the weighted sum method,
were introduced for the initial population of the GA. The proposed method was applied to a structural topology optimization
example and the results of the proposed method were compared with those of the traditional method using standard random
initialization for the initial population of the GA.
Keyword : Topology optimization, Multi-objective optimization problem, Genetic algorithm |