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Solving an Extended Double Row Layout Problem Using Multiobjective Tabu Search and Linear Programming

机译:使用多目标禁忌搜索和线性规划求解扩展的双行布局问题

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Facility layout problems have drawn much attention over the years, as evidenced by many different versions and formulations in the manufacturing context. This paper is motivated by semiconductor manufacturing, where the floor space is highly expensive (such as in a cleanroom environment) but there is also considerable material handling amongst machines. This is an integrated optimization task that considers both material movement and manufacturing area. Specifically, a new approach combining multiobjective tabu search with linear programming is proposed for an extended double row layout problem, in which the objective is to determine exact locations of machines in both rows to minimize material handling cost and layout area where material flows are asymmetric. First, a formulation of this layout problem is established. Second, an optimization framework is proposed that utilizes multiobjective tabu search and linear programming to determine a set of non-dominated solutions, which includes both sequences and positions of machines. This framework is applied to various manufacturing situations, and compared with an exact approach and a popular multiobjective genetic algorithm optimization algorithm. Experimental results show that the proposed approach is able to obtain sets of Pareto solutions that are far better than those obtained by the alternative approaches.
机译:多年来,设施布局问题引起了很多关注,制造环境中的许多不同版本和配方证明了这一点。本文是受半导体制造的推动,半导体制造的占地面积非常昂贵(例如在无尘室环境中),但是机器之间的材料处理也相当多。这是一项综合优化任务,同时考虑了物料移动和制造区域。具体而言,针对扩展的双排布局问题,提出了一种将多目标禁忌搜索与线性规划相结合的新方法,该方法的目的是确定两排机器的确切位置,以最大程度地减少物料搬运成本和物料流不对称的布局区域。首先,建立该布局问题的表述。其次,提出了一种优化框架,该框架利用多目标禁忌搜索和线性规划来确定一组非支配解,其中包括机器序列和位置。该框架适用于各种制造情况,并与精确方法和流行的多目标遗传算法优化算法进行了比较。实验结果表明,所提出的方法能够获得比替代方法更好的Pareto解集。

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