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Huma Naeem, A. Masood
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引用次数: 3

摘要

针对多目标机载威胁,提出了一种基于两阶段柔性动态决策支持的最优威胁评估和防御资源调度算法。该算法根据需要在两个目标函数之间进行切换,提供了灵活性和最优性,基于优先和减法防御策略。为了进一步提高解决方案的质量,我们将威胁评估和武器分配(TEWA)中使用的关键参数概述并划分为三大类(触发、调度和排序参数)。该算法采用多对多稳定婚姻算法(SMA)的一种变体来解决威胁评估(TE)和武器分配(WA)问题。在TE阶段,进行威胁排序和威胁资产配对。第二阶段是基于灵活的动态武器调度算法,允许使用射击-看-射策略进行多次交战,为一系列场景计算接近最优的解决方案。本文的分析部分给出了该算法在不同的离线场景下与另一种贪心算法相比的优缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A two-stage dynamic decision support based optimal threat evaluation and defensive resource scheduling algorithm for multi air-borne threats: Asset-based dynamic weapon scheduling using artificial intelligence techinques
This paper presents a two-stage flexible dynamic decision support based optimal threat evaluation and defensive resource scheduling algorithm for multi-target air-borne threats. The algorithm provides flexibility and optimality by swapping between two objective functions, based on preferential and subtractive defense strategies as and when required. To further enhance the solution quality, we outline and divide the critical parameters used in Threat Evaluation and Weapon Assignment (TEWA) into three broad categories (Triggering, Scheduling and Ranking parameters). Proposed algorithm uses a variant of many-to-many Stable Marriage Algorithm (SMA) to solve Threat Evaluation (TE) and Weapon Assignment (WA) problem. In TE stage, Threat Ranking and Threat-Asset pairing is done. Stage two is based on a flexible dynamic weapon scheduling algorithm, allowing multiple engagements using shoot-look-shoot strategy, to compute near-optimal solution for a range of scenarios. Analysis part of this paper presents the strengths and weaknesses of the proposed algorithm over an alternative greedy algorithm as applied to different offline scenarios.
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