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Rank-Cluster-and-Prune: An algorithm for generating clusters in complex set partitioning problems

机译:Rank-Cluster-and-prune:一种在复杂集合分区问题中生成集群的算法

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摘要

Clustering problems are often difficult to solve due to nonlinear cost functions and complicating constraints. Set partitioning formulations can help overcome these challenges, but at the cost of a very large number of variables. Therefore, techniques such as delayed column generation must be used to solve these large integer programs. The underlying pricing problem can suffer from the same challenges (non-linear cost, complicating constraints) as the original problem, however, making a mathematical programming approach intractable. Motivated by a real-world problem in printed circuit board (PCB) manufacturing, we develop a search-based algorithm (Rank-Cluster-and-Prune) as an alternative, present computational results for the PCB problem to demonstrate the tractability of our approach, and identify a broader class of clustering problems for which this approach can be used. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009
机译:由于非线性成本函数和复杂的约束,聚类问题通常难以解决。设置分区配方可以帮助克服这些挑战,但是以非常大量的变量的成本。因此,必须使用诸如延迟列生成的技术来解决这些大型整数程序。底层定价问题可能遭受与原始问题相同的挑战(非线性成本,使限制),然而,制造数学编程方法难以解返。通过印刷电路板(PCB)制造中的真实问题,我们开发了一种基于搜索的算法(秩-Cluster-and-Preune)作为替代方案,目前PCB问题的计算结果展示了我们方法的易行性,并确定可以使用这种方法的更广泛的聚类问题。 ©2009 Wiley期刊,Inc。海军研究后勤2009

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