Publications (3)2.98 Total impact
Article: A modified ant colony algorithm for the stacking sequence optimisation of a rectangular laminate[show abstract] [hide abstract]
ABSTRACT: This paper presents a modified Ant Colony Algorithm (ACA) called multi-city-layer ant colony algorithm (MCLACA). The research attention is focused on improving the computational efficiency in the stacking sequence optimisation of a laminated composite plate for maximum buckling load. A new operator, the so-called two point interchange, is introduced and proved to be effective for reducing the convergence time and enhancing the robustness in the MCLACA performance. The laminate optimisation is subject to balanced and symmetric layup with ply contiguous and strength constraints. In order to assess the MCLACA performance, a simply supported rectangular laminate plate, which was taken as numerical example in previous research using traditional ACA and genetic algorithm (GA) is chosen as a benchmark case study. Comparing with the ACA and GA results, it is shown that the presented MCLACA has better performance in terms of computational efficiency and robustness. To demonstrate the applicability of the MCLACA to a general case, an additional example of laminate optimisation has been taken with more design variables and five different boundary conditions by finite element analysis. KeywordsLaminate optimisation-Ant colony algorithm (ACA)-Multi-city-layer ant colony algorithm (MCLACA)Structural and Multidisciplinary Optimization 05/2012; 41(5):711-720. · 1.49 Impact Factor
Article: Ply stacking sequence optimization of composite laminate by permutation discrete particle swarm optimization[show abstract] [hide abstract]
ABSTRACT: Stacking sequence optimization (SSO) of laminate will greatly improve its mechanical properties without weight penalty. In this paper, a novel permutation discrete particle swarm optimization (PDPSO) method was proposed to perform SSO. To improve the efficiency of the algorithm, the concepts and techniques of valid/invalid exchange, checking memory and Self-escape were introduced into the PDPSO. In total 11 examples were presented. First, eight examples were carried out by employing the proposed method. The results show that the computational efficiency of PDPSO is greatly improved compared with standard discrete particle swarm optimization (SDPSO), and is comparable with that of gene rank crossover (GR) and partially mapped crossover (PMX). Then, three extra examples were presented, in which the outermost plies in the optimum design are not ±45° plies. The results show that the PDPSO has better stability and potential which demonstrate the better performance of PDPSO for laminates.Structural and Multidisciplinary Optimization 04/2012; 41(2):179-187. · 1.49 Impact Factor
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ABSTRACT: Optimal design of laminated composite stiffened panels of symmetric and balanced layup with different number of T-shape stiffeners is investigated and presented. The stiffened panels are simply supported and subjected to uniform biaxial compressive load. In the optimization for the maximum buckling load without weight penalty, the panel skin and the stiffened laminate stacking sequence, thickness and the height of the stiffeners are chosen as design variables. The optimization is carried out by applying an ant colony algorithm (ACA) with the ply contiguous constraint taken into account. The finite strip method is employed in the buckling analysis of the stiffened panels. The results shows that the buckling load increases dramatically with the number of stiffeners at first, and then has only a small improvement after the number of stiffeners reaches a certain value. An optimal layup of the skin and stiffener laminate has also been obtained by using the ACA. The methods presented in this paper should be applicable to the design of stiffened composite panels in similar loading conditions.Composite Structures.