4.7 Article

An improved constrained differential evolution using discrete variables (D-ICDE) for layout optimization of truss structures

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 42, Issue 20, Pages 7057-7069

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2015.04.072

Keywords

(mu plus lambda) Improved differential evolution (IDE); Archiving-based adaptive tradeoff model (ArATM); Improved (mu plus lambda) constrainted differential evolution (ICDE); Discrete-ICDE (D-ICDE); Discrete variables; Truss layout optimization

Funding

  1. Vietnam National Foundation for Science & Technology Development (NAFOSTED), Ministry of Science & Technology, under the basic research program [107.99-2014.11]

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Recently, an improved (mu + lambda) constrainted differential evolution (ICDE) has been proposed and proven to be robust and effective for solving constrainted optimization problems. However, so far, the ICDE has been developed mainly for continuous design variables, and hence it becomes inappropriate for solving layout truss optimization problems which contain both discrete and continuous variables. This paper hence fills this,gap by proposing a novel discrete variables handling technique and integrating it into original ICDE to give a so-called Discrete-ICDE (D-ICDE) for solving layout truss optimization problems. Objective functions of the optimization problems are minimum weights of the whole truss structures and constraints are stress, displacement and buckling limitations. Numerical examples of five classical truss problems are carried out and compared to other state-of-the-art optimization methods to illustrate the reliability and effectiveness of the proposed method. The D-ICDE's performance shows that it not only successfully handles discrete variables but also significantly improves the convergence of layout truss optimization problem. The D-ICDE is promising to extend for determining the optimal solution of other structural optimization problems which contain both discrete and continuous variables. (C) 2015 Elsevier Ltd. All rights reserved.

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