Efficient cross-district police dispatching is vital for timely emergency response, yet it faces complex constraints involving coupled inter-district routing, task sequencing, escort capacities, and mandatory transfers at makeshift police posts. This study formulates the Multi-district Police Dispatching and Path Planning Problem (MDPDPP) with makespan minimization. To address the problem’s hierarchical structure, we propose a Cooperative Iterated Greedy (CIG) algorithm. The problem is decomposed into district-level routing and capacity-constrained intra-district task scheduling, which are jointly optimized through a cooperative search mechanism. A capacity-aware decoding and local search strategy is further developed to capture the non-linear effects of escort capacity dynamics and mandatory detours. Computational experiments on a wide range of instances show that the proposed CIG algorithm consistently outperforms several state-of-the-art metaheuristics in terms of solution quality and robustness. Friedman statistical tests further confirm the statistical significance of the observed performance improvements, demonstrating the effectiveness of the proposed approach for complex multi-district police dispatching systems.
Xu et al. (Tue,) studied this question.
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