Department of Civil and Environmental Engineering, The University of Utah, Salt Lake City, Utah, United States of America.
Key Laboratory of Road Traffic Engineering of the Ministry of Education, Changsha University of Science and Technology, Changsha, Hunan, China.
PLoS One. 2018 Jun 14;13(6):e0198443. doi: 10.1371/journal.pone.0198443. eCollection 2018.
Various natural and manmade disasters during last decades have highlighted the need of further improving on governmental preparedness to emergency events, and a relief supplies distribution problem named Inventory Slack Routing Problem (ISRP) has received increasing attentions. In an ISRP, inventory slack is defined as the duration between reliefs arriving time and estimated inventory stock-out time. Hence, a larger inventory slack could grant more responsive time in facing of various factors (e.g., traffic congestion) that may lead to delivery lateness. In this study, the relief distribution problem is formulated as an optimization model that maximize the minimum slack among all dispensing sites. To efficiently solve this problem, we propose a two-stage approach to tackle the vehicle routing and relief allocation sub-problems. By analyzing the inter-relations between these two sub-problems, a new objective function considering both delivery durations and dispensing rates of demand sites is applied in the first stage to design the vehicle routes. A hierarchical routing approach and a sweep approach are also proposed in this stage. Given the vehicle routing plan, the relief allocation could be easily solved in the second stage. Numerical experiment with a comparison of multi-vehicle Traveling Salesman Problem (TSP) has demonstrated the need of ISRP and the capability of the proposed solution approaches.
过去几十年中的各种自然灾害和人为灾害突显了进一步提高政府应对紧急事件的准备能力的必要性，一种名为“库存松弛路径问题（ISRP）”的救灾物资分配问题引起了越来越多的关注。在 ISRP 中，库存松弛定义为救援物资到达时间和估计库存短缺时间之间的持续时间。因此，较大的库存松弛可以在面对各种可能导致延迟交付的因素（例如交通拥堵）时提供更多的响应时间。在这项研究中，将救援分配问题制定为一个优化模型，该模型最大化所有分发点中的最小松弛。为了有效地解决这个问题，我们提出了一种两阶段方法来解决车辆路径和救援分配子问题。通过分析这两个子问题之间的关系，在第一阶段应用了一个新的考虑需求点的交付时间和分配率的目标函数来设计车辆路径。在该阶段还提出了分层路由方法和清扫方法。给定车辆路径计划，第二阶段可以轻松地解决救援分配问题。通过与多车辆旅行商问题（TSP）的比较进行的数值实验证明了 ISRP 的必要性和所提出的解决方案方法的能力。
