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A fuzzy programming model for decentralization and drone utilization in urban humanitarian relief chains
Transportation Research Part E: Logistics and Transportation Review ( IF 8.3 ) Pub Date : 2025-01-20 , DOI: 10.1016/j.tre.2024.103949
Amirali Amirsahami, Farnaz Barzinpour, Mir Saman Pishvaee
Transportation Research Part E: Logistics and Transportation Review ( IF 8.3 ) Pub Date : 2025-01-20 , DOI: 10.1016/j.tre.2024.103949
Amirali Amirsahami, Farnaz Barzinpour, Mir Saman Pishvaee
The urgent need for rapid disaster response mechanisms, particularly in the event of earthquakes, is critical. In response to directives from the National Crisis Management Supreme Council, a plan has been initiated to establish distribution centers across all zones of Tehran, Iran, which signals a significant shift towards decentralization. However, land scarcity and road blockages hinder the full realization of a decentralized structure in certain zones. To address these challenges, two strategies have been proposed: facility expansion and drone-aided delivery. The integration of these strategies has led to the development of a novel structure, the hybrid decentralized humanitarian relief chain with simultaneous utilization of trucks and drones (HDHRC-TD). Mathematical optimization techniques are employed to model the distribution of relief items during the pre-disaster preparedness stage, especially in the critical first hours following an earthquake. The system is treated as a two-echelon network. Additionally, to account for the negative impact of uncertainty in road network connectivity, truck travel time is modeled as an uncertain parameter. A novel simulation-based bi-objective fuzzy chance-constrained programming (SBFCCP) model is introduced to manage this uncertainty. To ensure the model can be solved within a reasonable time frame, a hybrid metaheuristic algorithm, the modified NSGA-II with adaptive VNS algorithm (M−NSGA−II−AVNS), is employed. The facility expansion strategy reduces establishment costs to 25% of those of a fully decentralized system, while achieving 77% of its response time reduction. The drone-aided delivery strategy further enhances disaster response by improving access to more roads, significantly reducing total waiting times. Moreover, validation of the proposed model confirms its accuracy in managing uncertainty, further supporting the cost-effectiveness and resiliency of the proposed structure for urban disaster response.
中文翻译:
城市人道主义救援链中去中心化和无人机利用的模糊规划模型
迫切需要快速的灾害响应机制,尤其是在发生地震时。为响应国家危机管理最高委员会的指示,已启动一项计划,在伊朗德黑兰的所有地区建立配送中心,这标志着向权力下放的重大转变。然而,土地稀缺和道路堵塞阻碍了在某些区域完全实现去中心化结构。为了应对这些挑战,已经提出了两种策略:设施扩建和无人机辅助交付。这些策略的整合导致了一种新颖结构的发展,即同时使用卡车和无人机的混合去中心化人道主义救援链 (HDHRC-TD)。采用数学优化技术对灾前准备阶段救灾物资的分布进行建模,尤其是在地震发生后关键的最初几个小时内。该系统被视为两个梯队网络。此外,为了考虑道路网络连通性不确定性的负面影响,将卡车行驶时间建模为不确定参数。引入了一种新的基于仿真的双目标模糊机会约束规划 (SBFCCP) 模型来管理这种不确定性。为了确保模型可以在合理的时间范围内求解,采用了一种混合元启发式算法,即具有自适应 VNS 算法的改进的 NSGA-II (M-NSGA-II-AVNS)。设施扩展策略将建立成本降低到完全去中心化系统的 25%,同时实现了 77% 的响应时间缩短。无人机辅助交付策略通过改善更多道路的可达性,显著减少总等待时间,进一步加强了救灾响应。 此外,对所提出的模型的验证证实了其在管理不确定性方面的准确性,进一步支持了所提出的城市灾害响应结构的成本效益和弹性。
更新日期:2025-01-20
中文翻译:
![](https://scdn.x-mol.com/jcss/images/paperTranslation.png)
城市人道主义救援链中去中心化和无人机利用的模糊规划模型
迫切需要快速的灾害响应机制,尤其是在发生地震时。为响应国家危机管理最高委员会的指示,已启动一项计划,在伊朗德黑兰的所有地区建立配送中心,这标志着向权力下放的重大转变。然而,土地稀缺和道路堵塞阻碍了在某些区域完全实现去中心化结构。为了应对这些挑战,已经提出了两种策略:设施扩建和无人机辅助交付。这些策略的整合导致了一种新颖结构的发展,即同时使用卡车和无人机的混合去中心化人道主义救援链 (HDHRC-TD)。采用数学优化技术对灾前准备阶段救灾物资的分布进行建模,尤其是在地震发生后关键的最初几个小时内。该系统被视为两个梯队网络。此外,为了考虑道路网络连通性不确定性的负面影响,将卡车行驶时间建模为不确定参数。引入了一种新的基于仿真的双目标模糊机会约束规划 (SBFCCP) 模型来管理这种不确定性。为了确保模型可以在合理的时间范围内求解,采用了一种混合元启发式算法,即具有自适应 VNS 算法的改进的 NSGA-II (M-NSGA-II-AVNS)。设施扩展策略将建立成本降低到完全去中心化系统的 25%,同时实现了 77% 的响应时间缩短。无人机辅助交付策略通过改善更多道路的可达性,显著减少总等待时间,进一步加强了救灾响应。 此外,对所提出的模型的验证证实了其在管理不确定性方面的准确性,进一步支持了所提出的城市灾害响应结构的成本效益和弹性。