Adaptive chaotic particle swarm algorithm for isogeometric multi-objective size optimization of FG plates

Published on Aug 1, 2019in Structural and Multidisciplinary Optimization3.377
· DOI :10.1007/S00158-019-02238-2
Chao Wang7
Estimated H-index: 7
(Anhui University of Technology),
Tiantang Yu32
Estimated H-index: 32
(Hohai University)
+ 2 AuthorsTinh Quoc Bui54
Estimated H-index: 54
(TITech: Tokyo Institute of Technology)
Source
Abstract
An effective multi-objective optimization methodology that combines the isogeometric analysis (IGA) and adaptive chaotic particle swarm algorithm is presented for optimizing ceramic volume fraction (CVF) distribution of functionally graded plates (FGPs) under eigenfrequencies. The CVF distribution is represented by the B-spline basis function. Mechanical behaviors of FGPs are obtained with NURBS-based IGA and the recently developed simple first-order shear theory. The design variables are the CVFs at control points in the thickness direction, and the optimization objective is to minimize the mass of structure and maximize the first natural frequency. A recently developed multi-objective adaptive chaotic particle swarm algorithm with high efficiency is employed as an optimizer. All desirable features of the developed approach will be illustrated through four numerical examples, confirming its effectiveness and reliability.
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