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On Threshold BDDs and the Optimal Variable Ordering Problem

机译:关于阈值BDD和最佳变量排序问题

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Many combinatorial optimization problems can be formulated as 0/1 integer programs (0/1 Ips). The investigation of the structure of these problems raises the following tasks: count or enumerate the feasible solutions and find an optimal solution according to a given linear objective function. All these tasks can be accomplished using binary decision diagrams (BDDs), a very popular and effective datastructure in computational logics and hardware verification. We present a novel approach for these tasks which consists of an output-sensitive algorithm for building a BDD for a linear constraint (a so-called threshold BDD) and a parallel AND operation on threshold BDDs. In particular our algorithm is capable of solving knapsack problems, subset sum problems and multidimensional knapsack problems. BDDs are represented as a directed acyclic graph. The size of a BDD is the number of nodes of its graph. It heavily depends on the chosen variable ordering. Finding the optimal variable ordering is an NP-hard problem. We derive a 0/1 IP for finding an optimal variable ordering of a threshold BDD. This 0/1 IP formulation provides the basis for the computation of the variable ordering spectrum of a threshold function. We introduce our new tool azove 2.0 as an enhancement to azove 1.1 which is a tool for counting and enumerating 0/1 points. Computational results on benchmarks from the literature show the strength of our new method.
机译:许多组合优化问题可以制定为0/1整数程序(0/1 IP)。对这些问题的结构的调查提出了以下任务:计数或枚举可行的解决方案并根据给定的线性目标函数找到最佳解决方案。所有这些任务都可以使用二进制决策图(BDD),在计算逻辑和硬件验证中是一个非常流行和有效的数据结构。我们提出了一种用于这些任务的新方法,该方法包括用于构建用于线性约束(所谓的阈值BDD)的BDD的输出敏感算法和对阈值BDD的并行和操作。特别是我们的算法能够解决背包问题,子集和问题和多维背包问题。 BDD表示为定向的非循环图。 BDD的大小是其图表的节点数量。它大量取决于所选择的可变排序。找到最佳变量排序是一个难题的问题。我们派生了0/1 IP,用于查找阈值BDD的最佳变量排序。该0/1 IP配方提供了计算阈值函数的可变排序谱的基础。我们将我们的新工具Azove 2.0介绍为Azove 1.1的增强,这是一个用于计数和枚举0/1点的工具。从文献的基准测试结果表明了我们新方法的实力。

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