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Robust patrol strategies against attacks at dispersed heterogeneous locations

机译:强大的巡逻策略反对分散异构地点的攻击

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>We study a patrol problem where several patrollers move between heterogeneous locations dispersed throughout an area of interest in order to detect potential enemy attacks. To formulate an effective patrol policy, the patrollers must take into account travel time between locations, as well as location-specific attributes, such as time required for a patrol inspection, time required by an adversary to carry out an attack, and cost incurred due to an undetected attack. The patrol team wants to determine a robust patrol strategy that minimises the expected cost when, and if, an attack happens, regardless of where an intelligent enemy chooses to attack. For the case of a single patroller, we can compute the optimal solution via linear programming. For the case of multiple patrollers, we focus on efficient heuristic strategies based on set partitions and shortest paths.
机译:>我们研究了一个巡逻问题,其中几个巡逻队在分散在整个兴趣领域的异构地点之间移动,以检测潜在的敌人攻击。 为了制定有效的巡逻政策,巡逻队必须考虑地点之间的旅行时间,以及特定于位置的属性,例如巡逻检验所需的时间,对手进行攻击所需的时间,以及所需的费用 一个未被发现的攻击。 巡逻队希望确定一个强大的巡逻策略,最小化预期成本,如果攻击发生,无论智能敌人选择攻击。 对于单个巡逻人的情况,我们可以通过线性编程计算最佳解决方案。 对于多个巡逻人的情况,我们专注于基于Set分区和最短路径的高效启发式策略。

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