In this paper we deal with a practical problem that arises in military situations. The problem is to plan a path for one (or more) agents to reach a target without being detected by enemy sensors. Agents are not passive, rather they can (within limits) initiate actions which aid evasion, namely knockout (completely disable sensors) and confusion (reduce sensor detection probabilities). Agent actions are path dependent and time limited. Here by path dependent we mean that an agent needs to be sufficiently close to a sensor to knock it out. By time limited we mean that a limit is imposed on how long a sensor is knocked out or confused before it reverts back to its original operating state. The approach adopted breaks the continuous space in which agents move into a discrete space. This enables the problem to be represented (formulated) mathematically as a zero-one integer program with linear constraints. The advantage of representing the problem in this manner is that powerful commercial software optimisation packages exist to solve the problem to proven global optimality. Computational results are presented for a number of randomly generated test problems.
翻译:在本文中,我们处理的是军事局势中出现的实际问题。 问题在于为一个( 或更多) 物剂规划一条路径, 使其在没有被敌国传感器探测到的情况下达到目标。 物剂不是被动的, 而是可以( 在限度内) 发起逃避援助的行动, 即击倒( 完全禁用感应器) 和混乱( 降低感应检测概率) 。 物剂行动取决于路径, 时间有限 。 在这里, 取决于路径, 我们意味着一个物剂需要足够接近感应器, 才能把它击倒。 时间有限, 我们意味着在传感器恢复到其原始运行状态之前, 限制传感器被击倒或混淆的时间。 所采用的方法打破了它们移动到离散空间的连续空间。 这使得问题能够以数学形式( 公式化), 作为带有线性限制的零一整式程序。 代表问题的优势是, 强大的商业软件优化软件包的存在可以解决问题, 从而证明它具有全球最佳性。 计算结果是为了随机产生的一些测试问题。