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 initiate actions which aid evasion. They can knockout, completely disable, sensors. They can also confuse sensors, so reduce sensor detection probabilities. Agent actions are path dependent and time limited. 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 formulated 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. A heuristic for the problem based on successive shortest paths is also presented. 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一个实际问题。 问题在于为一个或多个物剂规划一条路径, 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, 而是可以启动帮助规避的行动。 它们可以击退, 完全禁用, 传感器。 它们也可以混淆传感器, 从而降低感官检测概率。 物剂行动取决于路径和时间限制 。 从路径上看, 我们意味着一个物剂需要足够接近传感器才能把它击倒。 时间有限, 我们意味着在传感器恢复到原始运行状态之前, 限制传感器被击倒或被混淆的时间。 所采用的方法打破了物剂移动到离散空间的持续空间。 这使得问题能够形成为带有线性限制的零一整程序。 以这种方式代表问题的优势是, 强大的商业软件优化软件包的存在可以解决问题, 从而证明是全球最佳的。 基于连续最短路径的问题的杂乱无常态。 计算结果显示为随机产生的试验问题。