Packing Groups of Items into Multiple Knapsacks

Lin Chen, Guochuan Zhang
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引用次数: 14

Abstract

We consider a natural generalization of the classical multiple knapsack problem in which instead of packing single items we are packing groups of items. In this problem, we have multiple knapsacks and a set of items partitioned into groups. Each item has an individual weight, while the profit is associated with groups rather than items. The profit of a group can be attained if and only if every item of this group is packed. Such a general model finds applications in various practical problems, e.g., delivering bundles of goods. The tractability of this problem relies heavily on how large a group could be. Deciding if a group of items of total weight 2 could be packed into two knapsacks of unit capacity is already NP-hard and it thus rules out a constant-approximation algorithm for this problem in general. We then focus on the parameterized version where the total weight of items in each group is bounded by a factor δ of the total capacity of all knapsacks. Both approximation and inapproximability results with respect to δ are derived. We also show that, depending on whether the number of knapsacks is a constant or part of the input, the approximation ratio for the problem, as a function on δ, changes substantially, which has a clear difference from the classical multiple knapsack problem.
将物品打包成多个背包
我们考虑了经典多重背包问题的一个自然推广,其中我们不是打包单个物品而是打包物品群。在这个问题中,我们有多个背包和一组被分成组的物品。每个项目都有一个单独的权重,而利润是与组而不是项目相关联的。当且仅当一个群体的每一项都被打包时,这个群体的利润才能实现。这样一个通用模型在各种实际问题中都有应用,例如,运送成捆货物。这个问题的可处理性在很大程度上取决于团队的规模。决定一组总重量为2的物品是否可以装入两个单位容量的背包已经是np困难的,因此它通常排除了这个问题的常数近似算法。然后,我们将重点放在参数化版本上,其中每组物品的总重量由所有背包总容量的因子δ限定。导出了δ的近似和不近似结果。我们还表明,根据背包的数量是常数还是输入的一部分,问题的近似比率作为δ的函数会发生实质性变化,这与经典的多重背包问题有明显区别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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