Intercepting a criminal using limited police resources presents a significant challenge in dynamic crime environments, where the criminal's location continuously changes over time. The complexity is further heightened by the vastness of the transportation network. To tackle this problem, we propose a layered graph representation, in which each time step is associated with a duplicate of the transportation network. For any given set of attacker strategies, a near-optimal defender strategy is computed using the A-Star heuristic algorithm applied to the layered graph. The defender's goal is to maximize the probability of successful interdiction. We evaluate the performance of the proposed method by comparing it with a Mixed-Integer Linear Programming (MILP) approach used for the defender. The comparison considers both computational efficiency and solution quality. The results demonstrate that our approach effectively addresses the complexity of the problem and delivers high-quality solutions within a short computation time.

翻译：在动态犯罪环境中，利用有限的警力资源拦截罪犯是一项重大挑战，因为罪犯的位置随时间不断变化。交通网络的广阔性进一步加剧了问题的复杂性。为解决这一问题，我们提出了一种分层图表示方法，其中每个时间步都与交通网络的一个副本相关联。对于任意给定的攻击者策略集合，通过在分层图上应用A-Star启发式算法，可以计算出接近最优的防御者策略。防御者的目标是最大化成功拦截的概率。我们通过将所提方法与用于防御者的混合整数线性规划方法进行比较，评估了该方法的性能。比较考虑了计算效率和求解质量两方面。结果表明，我们的方法能有效应对问题的复杂性，并在较短计算时间内提供高质量的解决方案。