Simultaneous optimization of the topology and geometry of a two-dimensional framed structure using an SA/GA hybrid optimization method

Yuichiro Sakamoto, Yasuhiro Bonkobara, Takahiro Kondou

Research output: Contribution to journalArticle

Abstract

A hybrid optimization method using simulated annealing (SA) and a genetic algorithm (GA) developed in a previous study is improved in order to achieve high computational performance. The previous method, in which the genetic operations for generating initial search solutions of the next generation are introduced into the computation process of multi-point SA, can efficiently and globally compute Pareto-optimal solutions, as compared to SA using a re-annealing method. However, a large number of Pareto-optimal solutions exceeding the acceptable amount of computer memory may be obtained. In the proposed method, in order to effectively store Pareto-optimal solutions in computer memory, all obtained solutions are classified according to topology type, and those that should be stored are selected from each topology group. In addition, selection methods based on four criteria are newly proposed in order to improve the convergence of solutions and to maintain their diversity. The proposed SA/GA hybrid algorithm for simultaneous optimization of the topology and geometry of a two-dimensional framed structure is applied to a two-objective optimization problem of minimizing the total weight and maximizing the first natural frequency under displacement and stress constraints. The validity of the proposed methods is confirmed through performance evaluation based on the Wilcoxon rank-sum test.

Original languageEnglish
Pages (from-to)3454-3468
Number of pages15
JournalNihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
Volume77
Issue number781
Publication statusPublished - 2011

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Simulated annealing
Genetic algorithms
Topology
Geometry
Data storage equipment
Natural frequencies
Annealing

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Mechanics of Materials
  • Industrial and Manufacturing Engineering

Cite this

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title = "Simultaneous optimization of the topology and geometry of a two-dimensional framed structure using an SA/GA hybrid optimization method",
abstract = "A hybrid optimization method using simulated annealing (SA) and a genetic algorithm (GA) developed in a previous study is improved in order to achieve high computational performance. The previous method, in which the genetic operations for generating initial search solutions of the next generation are introduced into the computation process of multi-point SA, can efficiently and globally compute Pareto-optimal solutions, as compared to SA using a re-annealing method. However, a large number of Pareto-optimal solutions exceeding the acceptable amount of computer memory may be obtained. In the proposed method, in order to effectively store Pareto-optimal solutions in computer memory, all obtained solutions are classified according to topology type, and those that should be stored are selected from each topology group. In addition, selection methods based on four criteria are newly proposed in order to improve the convergence of solutions and to maintain their diversity. The proposed SA/GA hybrid algorithm for simultaneous optimization of the topology and geometry of a two-dimensional framed structure is applied to a two-objective optimization problem of minimizing the total weight and maximizing the first natural frequency under displacement and stress constraints. The validity of the proposed methods is confirmed through performance evaluation based on the Wilcoxon rank-sum test.",
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