{"title":"具有需求优先权的多期应急资源分配问题的灵活分区政策","authors":"Xiaofeng Xu;Ziru Lin;Xiang Li;Wanli Yi;Witold Pedrycz","doi":"10.1109/TSMC.2024.3443116","DOIUrl":null,"url":null,"abstract":"To address responsiveness, time-dependence, and limited emergency supply issues, we introduce a new flexible districting policy, aiming to improve satisfaction in multiperiod emergency resource allocation (MPERA), and set demand priorities to guarantee allocation balance in resource-limited scenarios. The modeling and solution process involves the following: 1) formulating a mixed-integer programming (MILP) model for MPERA with demand priority (MPERA-DP), aiming to maximize utility considering the transportation cost, districting change, and penalty for unsatisfied demand and 2) incorporating the justifiable granularity principle (JGP) and particle swarm optimization (PSO) into the brand-and-price (B&P) algorithm for initial districting and allocating decisions to improve the solution quality and calculation speed. The results of the experiments show that 1) the JGP-PSO-B&P algorithm achieves superior efficiency in terms of optimality and convergence for large-scale cases. This algorithm could improve the optimality by 13.42% compared with that of the JGP-PSO algorithm, 13.15% compared with that of the B&P algorithm, and 28.18% compared with that of the PSO algorithm, on average; 2) the MPERA-DP model with flexible districting policy outperforms flexible MPERA without demand priority, emergency resource allocation with rescheduling (ERAR) and fixed emergency resource allocation with demand priority (FERA-DP), improving the utility by 20.56%, 5.14% and 41.84%, respectively; and 3) the scheme efficiency is influenced by the desirable satisfaction deviation, and when set to 0.6, it allows for the optimization of both demand satisfaction and utility.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":null,"pages":null},"PeriodicalIF":8.6000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Flexible Districting Policy for the Multiperiod Emergency Resource Allocation Problem With Demand Priority\",\"authors\":\"Xiaofeng Xu;Ziru Lin;Xiang Li;Wanli Yi;Witold Pedrycz\",\"doi\":\"10.1109/TSMC.2024.3443116\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To address responsiveness, time-dependence, and limited emergency supply issues, we introduce a new flexible districting policy, aiming to improve satisfaction in multiperiod emergency resource allocation (MPERA), and set demand priorities to guarantee allocation balance in resource-limited scenarios. The modeling and solution process involves the following: 1) formulating a mixed-integer programming (MILP) model for MPERA with demand priority (MPERA-DP), aiming to maximize utility considering the transportation cost, districting change, and penalty for unsatisfied demand and 2) incorporating the justifiable granularity principle (JGP) and particle swarm optimization (PSO) into the brand-and-price (B&P) algorithm for initial districting and allocating decisions to improve the solution quality and calculation speed. The results of the experiments show that 1) the JGP-PSO-B&P algorithm achieves superior efficiency in terms of optimality and convergence for large-scale cases. This algorithm could improve the optimality by 13.42% compared with that of the JGP-PSO algorithm, 13.15% compared with that of the B&P algorithm, and 28.18% compared with that of the PSO algorithm, on average; 2) the MPERA-DP model with flexible districting policy outperforms flexible MPERA without demand priority, emergency resource allocation with rescheduling (ERAR) and fixed emergency resource allocation with demand priority (FERA-DP), improving the utility by 20.56%, 5.14% and 41.84%, respectively; and 3) the scheme efficiency is influenced by the desirable satisfaction deviation, and when set to 0.6, it allows for the optimization of both demand satisfaction and utility.\",\"PeriodicalId\":48915,\"journal\":{\"name\":\"IEEE Transactions on Systems Man Cybernetics-Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.6000,\"publicationDate\":\"2024-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Systems Man Cybernetics-Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10659155/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Systems Man Cybernetics-Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10659155/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Flexible Districting Policy for the Multiperiod Emergency Resource Allocation Problem With Demand Priority
To address responsiveness, time-dependence, and limited emergency supply issues, we introduce a new flexible districting policy, aiming to improve satisfaction in multiperiod emergency resource allocation (MPERA), and set demand priorities to guarantee allocation balance in resource-limited scenarios. The modeling and solution process involves the following: 1) formulating a mixed-integer programming (MILP) model for MPERA with demand priority (MPERA-DP), aiming to maximize utility considering the transportation cost, districting change, and penalty for unsatisfied demand and 2) incorporating the justifiable granularity principle (JGP) and particle swarm optimization (PSO) into the brand-and-price (B&P) algorithm for initial districting and allocating decisions to improve the solution quality and calculation speed. The results of the experiments show that 1) the JGP-PSO-B&P algorithm achieves superior efficiency in terms of optimality and convergence for large-scale cases. This algorithm could improve the optimality by 13.42% compared with that of the JGP-PSO algorithm, 13.15% compared with that of the B&P algorithm, and 28.18% compared with that of the PSO algorithm, on average; 2) the MPERA-DP model with flexible districting policy outperforms flexible MPERA without demand priority, emergency resource allocation with rescheduling (ERAR) and fixed emergency resource allocation with demand priority (FERA-DP), improving the utility by 20.56%, 5.14% and 41.84%, respectively; and 3) the scheme efficiency is influenced by the desirable satisfaction deviation, and when set to 0.6, it allows for the optimization of both demand satisfaction and utility.
期刊介绍:
The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.