Amirali Amirsahami, Farnaz Barzinpour, Mir Saman Pishvaee
{"title":"A fuzzy programming model for decentralization and drone utilization in urban humanitarian relief chains","authors":"Amirali Amirsahami, Farnaz Barzinpour, Mir Saman Pishvaee","doi":"10.1016/j.tre.2024.103949","DOIUrl":null,"url":null,"abstract":"The urgent need for rapid disaster response mechanisms, particularly<ce:hsp sp=\"0.25\"></ce:hsp>in the event of<ce:hsp sp=\"0.25\"></ce:hsp>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,<ce:hsp sp=\"0.25\"></ce:hsp>which signals<ce:hsp sp=\"0.25\"></ce:hsp>a significant shift towards decentralization. However, land scarcity and road blockages hinder the<ce:hsp sp=\"0.25\"></ce:hsp>full realization of<ce:hsp sp=\"0.25\"></ce:hsp>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.<ce:hsp sp=\"0.25\"></ce:hsp>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.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"120 1","pages":""},"PeriodicalIF":8.3000,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1016/j.tre.2024.103949","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The urgent need for rapid disaster response mechanisms, particularlyin the event ofearthquakes, 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 signalsa significant shift towards decentralization. However, land scarcity and road blockages hinder thefull realization ofa 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.
期刊介绍:
Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management.
Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.