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Approximation Algorithms for a Two-Phase Knapsack Problem

机译:两阶段背包问题的近似算法

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We consider a natural generalization of the knapsack problem and the multiple knapsack problem, which has two phases of packing decisions. In this problem, we have a set of items, several small knapsacks called boxes, and a large knapsack called container. Each item has a size and profit, each box has a size and the container has a capacity. The first phase is to select some items to pack into the boxes, and the second phase is to select the boxes (each includes some packed items) to pack into the container. The total profit of the problem is determined by the items that are selected and packed into the container within some packed box, and the objective is to maximize the total profit. This problem is motivated by various practical applications, e.g., in logistics. It is a generalization of the multiple knapsack problem, and hence is strongly NP-hard. We mainly propose three approximation algorithms for it. Particularly, the first one is a 1/4 -approximation algorithm based on its linear programming relaxation; the second one is based on applying the algorithms for the multiple knapsack problem and the knapsack problem, and has an approximation ratio 1/3 - ∈ for any small enough ∈ > 0. We finally provide a polynomial time approximation scheme for this problem.
机译:我们考虑背包问题和多重背包问题的自然概括,这有两个阶段的包装决策。在这个问题中,我们有一组项目,几个称为箱子的小背包和一个称​​为容器的大背包。每个项目都有一个大小和利润,每个盒子都有一个大小,容器有一个容量。第一阶段是选择一些要包装到盒子中的物品,第二阶段是选择要包装到容器中的盒子(每个盒子都包括一些包装好的物品)。问题的总利润由选择并包装到包装盒中的容器中的物品确定,目标是使总利润最大化。该问题是由例如物流中的各种实际应用引起的。它是多背包问题的推广,因此具有很强的NP难度。我们主要针对它提出三种近似算法。特别地,第一个是基于线性规划松弛的1/4近似算法。第二种是基于将算法应用于多重背包问题和背包问题的,对于任何足够小的ε> 0,其近似比率为1/3-ε。最后,我们针对此问题提供了多项式时间近似方案。

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