Al3105-St14双层薄板重量最小化及成形性改善的多目标禁忌搜索算法

M. Ehsanifar, H. Momeni, N. Hamta, A. Nezamabadi
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引用次数: 0

摘要

如今,随着双层金属板在不同工业领域的应用越来越广泛,为了达到理想的性能,每一层的精确规格是非常重要的。为了预测板料在不同成形方式下的行为,确定断裂极限和颈缩,采用了成形极限图的概念。具有目标函数和重要参数的优化问题旨在找到Al3105-St14双层金属板贡献者的最优厚度。最优点是板材的可成形性达到最大程度,其重量达到最小程度。本文采用多目标禁忌搜索算法对所考虑的问题进行优化。最后,利用禁忌搜索算法推导出Pareto前沿,并与遗传算法求解结果进行了比较。对比发现,禁忌搜索算法在Mean Ideal Distance、Spacing、Pareto front的非均匀性、CPU时间等方面优于遗传算法。
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Multi-Objective Tabu Search Algorithm to Minimize Weight and Improve Formability of Al3105-St14 Bi-Layer Sheet
Nowadays, with extending applications of bi-layer metallic sheets in different industrial sectors, accurate specification of each layer is very prominent to achieve desired properties. In order to predict behavior of sheets under different forming modes and determining rupture limit and necking, the concept of Forming Limit Diagram (FLD) is used. Optimization problem with objective functions and important parameters aims to find optimal thickness for each of Al3105-St14 bi-layer metallic sheet contributors. Optimized point is achieved where formability of the sheet approaches to maximum extent and its weight to minimum extent. In this paper, multi-objective Tabu search algorithm is employed to optimize the considered problem. Finally, derived Pareto front using Tabu search algorithm is presented and results are compared with the solutions obtained from genetic algorithm. Comparison revealed that Tabu search algorithm provides better results than genetic algorithm in terms of Mean Ideal Distance, Spacing, non-uniformity of Pareto front and CPU time.
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