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Identifying sufficient deception in military logistics

机译:识别军事后勤中的欺骗行为

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In the context of modern warfare, military forces are faced with challenges that threaten their power projection operations. Adversarial strategies could hinder the actions of the forces within operational areas by inferring and anticipating a military's potential mission objectives including military logistics and transportation activities. Thus, this research investigates the potential ways of incorporating two military deception strategies into the military logistics decision making process: (i) falsifying signifies including empty convoys on routes on which commodities are being hauled, and (ii) hiding refers to concealing routes in the logistics network. Assuming that the adversaries can monitor the shipments in the transportation network, we develop a two-stage integer linear programming model that quantifies the sufficient amounts of each deception needed to deceive the adversaries. In addition, the mathematical model accurately captures several other military logistics challenges, such as satisfying the demands for military commodities at destinations subject to limited capacities at supply points, deciding the best route option, and respecting the time limit constraint. However, the two-stage model is non-convex and therefore, reformulation and linearization steps are applied to convert it to a convex single-stage model. Due to the computational complexity in solving the single-stage model for realistic-size instances, two greedy heuristics are developed that can efficiently solve those instances. Moreover, the computational experiments reveal that the greedy heuristics obtain near optimal solutions when compared to the solutions of the smaller instances solved to optimality via a commercial solver. (C) 2019 Elsevier Ltd. All rights reserved.
机译:在现代战争的背景下,军队面临着威胁其力量投射行动的挑战。对抗策略可能会通过推断和预测军队的潜在任务目标(包括军事后勤和运输活动)来阻碍部队在行动区域内的行动。因此,本研究调查了将两种军事欺骗策略纳入军事后勤决策过程的潜在方式:(i)伪造表示在运输货物的路线上包括空的车队,(ii)隐蔽是指在货物运输路线中隐藏路线物流网络。假设对手可以监视运输网络中的货物,我们开发了一个两阶段整数线性规划模型,该模型量化了欺骗对手所需的每种欺骗的足够数量。此外,该数学模型可以准确地捕获其他军事后勤挑战,例如满足供应点能力受限的目的地对军事商品的需求,确定最佳路线选择以及遵守时限约束。但是,两阶段模型是非凸模型,因此,应用了重构和线性化步骤将其转换为凸面单阶段模型。由于在求解实际大小的实例的单阶段模型时的计算复杂性,因此开发了两种可以有效求解这些实例的贪婪启发式算法。此外,计算实验表明,贪婪启发式算法与通过商业解算器求解为最优的较小实例的解相比,可获得接近最优的解。 (C)2019 Elsevier Ltd.保留所有权利。

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