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Structural and Multidisciplinary Optimization

, Volume 31, Issue 1, pp 49–59 | Cite as

A double-distribution statistical algorithm for composite laminate optimization

  • Laurent GrossetEmail author
  • Rodolphe LeRiche
  • Raphael T. Haftka
Research Paper

Abstract

The paper proposes a new evolutionary algorithm termed Double-Distribution Optimization Algorithm (DDOA). DDOA belongs to the family of estimation of distribution algorithms (EDA) that build a statistical model of promising regions of the design space based on sets of good points and use it to guide the search. The efficiency of these algorithms is heavily dependent on the model accuracy. In this work, a generic framework for enhancing the model accuracy by incorporating statistical variable dependencies is presented. The proposed algorithm uses two distributions simultaneously: the marginal distributions of the design variables, complemented by the distribution of physically meaningful auxiliary variables. The combination of the two generates more accurate distributions of promising regions at a low computational cost. The paper demonstrates the efficiency of DDOA for three laminate optimization problems where the design variables are the fiber angles, and the auxiliary variables are integral quantities called lamination parameters. The results show that the reliability of DDOA in finding the optima is greater than that of simple EDA and a standard genetic algorithm, and that its advantage increases with the problem dimension.

Keywords

Stacking sequence optimization Composite laminate Evolutionary computation Estimation of distribution algorithms Lamination parameters 

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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Laurent Grosset
    • 1
    Email author
  • Rodolphe LeRiche
    • 3
  • Raphael T. Haftka
    • 2
  1. 1.SMSÉcole des Mines de Saint-ÉtienneFrance
  2. 2.Department of Mechanical and Aerospace EngineeringUniversity of FloridaGainesvilleUSA
  3. 3.CNRS UMR 5146/SMSÉcole des Mines de Saint-ÉtienneSaint-ÉtienneFrance

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