Solving an Extended Double Row Layout Problem Using Multiobjective Tabu Search and Linear Programming
Solving an Extended Double Row Layout Problem Using Multiobjective Tabu Search and Linear Programming
复制标题
使用多目标禁忌搜索和线性规划解决扩展双行布局问题
DOI：
10.1109/tase.2014.2304471
复制
发表时间：
2014-03
影响因子：
5.6
通讯作者：
Smith Alice E.
中科院分区：
文献类型：
--
作者：
Zuo Xingquan;Murray Chase C.;Smith Alice E.
多年来，工厂布局问题引起了人们的极大关注，制造业中的许多不同版本和配方都证明了这一点。这篇论文是由半导体制造业推动的，半导体制造业的占地面积非常昂贵(例如在洁净室环境中)，但机器之间也有相当大的材料处理。这是一项综合考虑物料运动和制造区域的优化任务。具体地说，提出了一种多目标禁忌搜索与线性规划相结合的方法来解决扩展的双层排样问题，该问题的目标是确定两排机器的准确位置，以最小化物流不对称的物料搬运成本和排样面积。首先，建立了该布局问题的公式。其次，提出了一个优化框架，利用多目标禁忌搜索和线性规划来确定一组既包括机器顺序又包括机器位置的非支配解。将该框架应用于各种生产情况，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，该方法能够得到比其他方法更好的Pareto解集。
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.
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DOI：
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发表时间：
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期刊：
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影响因子：
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影响因子：
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发表时间：
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期刊：
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影响因子：
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