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A comparison of three population-based optimization techniques for the design of composite sandwich materials

Lookup NU author(s): Craig Hudson, Dr Joe Carruthers, Professor Mark RobinsonORCiD

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by Sage, 2011.

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Abstract

Three population-based optimization techniques - particle swarm optimization, ant colony optimization, and simulated annealing - are applied to the multi-objective design of sandwich materials. The formulation of the algorithms is described, along with metrics for quantifying their performance. For the case study considered of a sandwich beam in bending, it is shown that the ant colony technique out-performs the other two algorithms with respect to identifying optimal geometries, materials, and lay-ups for a stiff sandwich in which low mass and low cost are the design objectives. The particle swarm and simulated annealing algorithms were found to have particular difficulties in handling the optimization of multi-ply oriented fiber-reinforced polymer facing laminates.

Publication metadata

Author(s): Hudson CW, Carruthers JJ, Robinson AM

Publication type: Article

Publication status: Published

Journal: Journal of Sandwich Structures and Materials

Year: 2011

Volume: 13

Issue: 2

Pages: 213-235

Print publication date: 01/03/2011

Online publication date: 21/05/2010

Date deposited: 03/05/2011

ISSN (print): 1099-6362

ISSN (electronic): 1530-7972

Publisher: Sage

URL: http://dx.doi.org/10.1177/1099636210369205

DOI: 10.1177/1099636210369205

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