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In this paper we present a new combinatorial problem, called minmax multidimensional knapsack problem (MKP), motivated by a military logistics problem. The logistics problem is a two‐period, two‐level, chance‐constrained problem with recourse. We show that the MKP is NP‐hard and develop a practically efficient combinatorial algorithm for solving it. We also show that under some reasonable assumptions regarding the operational setting of the logistics problem, the chance‐constrained optimization problem is decomposable into a series of MKPs that are solved separately. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007  相似文献   
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We consider a reliable network design problem under uncertain edge failures. Our goal is to select a minimum‐cost subset of edges in the network to connect multiple terminals together with high probability. This problem can be seen as a stochastic variant of the Steiner tree problem. We propose two scenario‐based Steiner cut formulations, study the strength of the proposed valid inequalities, and develop a branch‐and‐cut solution method. We also propose an LP‐based separation for the scenario‐based directed Steiner cut inequalities using Benders feasibility cuts, leveraging the success of the directed Steiner cuts for the deterministic Steiner tree problem. In our computational study, we test our branch‐and‐cut method on instances adapted from graphs in SteinLib Testdata Library with up to 100 nodes, 200 edges, and 17 terminals. The performance of our branch‐and‐cut method demonstrates the strength of the scenario‐based formulations and the benefit from adding the additional valid inequalities that we propose. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 321–334, 2015  相似文献   
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应用随机机会约束规划理论,研究了指定区域无源定位系统布站优化问题。针对无源定位站点部署研究存在的局限,从误差准则、截获准则和协同准则出发,建立了无源定位系统布站优化的随机机会约束模型。对三站定位问题进行了仿真,利用混合智能算法得到了不同情况下的最优布站策略。  相似文献   
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中央八项规定的出台给警卫工作带来了前所未有的挑战,即:减少“硬性”控制措施,能否经得起严峻安全形势的考验,确保警卫安全;接受公众和舆论的监督,能否提交合格“答卷”,展示警卫部队的良好形象。同时,中央八项规定也为推动警卫工作模式创新、警卫战斗力建设、警卫工作立法、警卫工作理念和作风转变提供了难得的机遇。  相似文献   
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We consider the problem of determining the capacity to assign to each arc in a given network, subject to uncertainty in the supply and/or demand of each node. This design problem underlies many real‐world applications, such as the design of power transmission and telecommunications networks. We first consider the case where a set of supply/demand scenarios are provided, and we must determine the minimum‐cost set of arc capacities such that a feasible flow exists for each scenario. We briefly review existing theoretical approaches to solving this problem and explore implementation strategies to reduce run times. With this as a foundation, our primary focus is on a chance‐constrained version of the problem in which α% of the scenarios must be feasible under the chosen capacity, where α is a user‐defined parameter and the specific scenarios to be satisfied are not predetermined. We describe an algorithm which utilizes a separation routine for identifying violated cut‐sets which can solve the problem to optimality, and we present computational results. We also present a novel greedy algorithm, our primary contribution, which can be used to solve for a high quality heuristic solution. We present computational analysis to evaluate the performance of our proposed approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 236–246, 2016  相似文献   
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