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Dynamic programming based algorithms for the discounted {0-1} knapsack problem

机译:折扣{0-1}背包问题的基于动态规划的算法

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The discounted {0-1} knapsack problem (DKP) is an extension of the classical {0-1} knapsack problem (KP) that consists of selecting a set of item groups where each group includes three items and at most one of the three items can be selected. The DKP is more challenging than the KP because four choices of items in an item group diversify the selection of the items. Consequently, it is not possible to solve the DKP based on a classical definition of a core consisting of a small number of relevant variables. This paper partitions the DKP into several easier sub-problems to achieve problem reductions by imitating the core concept of the KP to derive an alternative core for the DKP. Numerical experiments with DP-based algorithms are conducted to evaluate the effectiveness of the problem partition by solving the partitioned problem and the original problem based on different types of DKP instances.
机译:折扣的{0-1}背包问题(DKP)是经典{0-1}背包问题(KP)的扩展,包括选择一组项目组,其中每个组包括三个项目,三个项目中最多一个可以选择项目。 DKP比KP更具挑战性,因为项目组中的四个项目选择使项目的选择多样化。因此,不可能基于由少量相关变量组成的核心的经典定义来求解DKP。本文通过模仿KP的核心概念来推导DKP的替代核心,从而将DKP划分为几个更简单的子问题,以减少问题。进行了基于DP的算法的数值实验,以通过解决基于不同类型DKP实例的分区问题和原始问题来评估问题分区的有效性。

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