{"title":"紧急任务中基于局部搜索的联盟形成启发法","authors":"Miao Guo;Bin Xin;Yipeng Wang;Jie Chen","doi":"10.1109/TSMC.2024.3443860","DOIUrl":null,"url":null,"abstract":"This article focuses on the coalition formation (CF) problem in urgent missions, e.g., disaster rescue, where coalition members should reach mission locations quickly. A mathematical model is first constructed to minimize the latest arrival time of coalition members, considering the capability requirements of missions, nonredundant agents in coalitions, etc. Then, incorporating the benefits in both the diversity of random search and the effectiveness of utilizing problem knowledge, a local-search-based heuristic is put forward to solve the CF problem. An initial solution is incrementally constructed by prioritizing agents with shorter movement times for missions with higher-remaining capability requirements. Additionally, two types of neighborhood search operators, namely, the tabu-based one-to-one swap and the destroy and repair operators, are proposed to search the solution space from two perspectives, i.e., “adjustment” and “reconstruction.” To solve the problem effectively and efficiently, the former excludes certain agent-exchange combinations that do not improve the current solution, while the latter consists of multiple heuristic rules extracted from the correlation among different model elements. Experimental results have demonstrated that the proposed method surpasses several advanced methods across various scenarios regarding multiple factors, such as the number of agents, the number of missions, and the demand-supply ratio on capabilities.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":null,"pages":null},"PeriodicalIF":8.6000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Local-Search-Based Heuristic for Coalition Formation in Urgent Missions\",\"authors\":\"Miao Guo;Bin Xin;Yipeng Wang;Jie Chen\",\"doi\":\"10.1109/TSMC.2024.3443860\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article focuses on the coalition formation (CF) problem in urgent missions, e.g., disaster rescue, where coalition members should reach mission locations quickly. A mathematical model is first constructed to minimize the latest arrival time of coalition members, considering the capability requirements of missions, nonredundant agents in coalitions, etc. Then, incorporating the benefits in both the diversity of random search and the effectiveness of utilizing problem knowledge, a local-search-based heuristic is put forward to solve the CF problem. An initial solution is incrementally constructed by prioritizing agents with shorter movement times for missions with higher-remaining capability requirements. Additionally, two types of neighborhood search operators, namely, the tabu-based one-to-one swap and the destroy and repair operators, are proposed to search the solution space from two perspectives, i.e., “adjustment” and “reconstruction.” To solve the problem effectively and efficiently, the former excludes certain agent-exchange combinations that do not improve the current solution, while the latter consists of multiple heuristic rules extracted from the correlation among different model elements. Experimental results have demonstrated that the proposed method surpasses several advanced methods across various scenarios regarding multiple factors, such as the number of agents, the number of missions, and the demand-supply ratio on capabilities.\",\"PeriodicalId\":48915,\"journal\":{\"name\":\"IEEE Transactions on Systems Man Cybernetics-Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.6000,\"publicationDate\":\"2024-09-02\",\"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/10663079/\",\"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/10663079/","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}
A Local-Search-Based Heuristic for Coalition Formation in Urgent Missions
This article focuses on the coalition formation (CF) problem in urgent missions, e.g., disaster rescue, where coalition members should reach mission locations quickly. A mathematical model is first constructed to minimize the latest arrival time of coalition members, considering the capability requirements of missions, nonredundant agents in coalitions, etc. Then, incorporating the benefits in both the diversity of random search and the effectiveness of utilizing problem knowledge, a local-search-based heuristic is put forward to solve the CF problem. An initial solution is incrementally constructed by prioritizing agents with shorter movement times for missions with higher-remaining capability requirements. Additionally, two types of neighborhood search operators, namely, the tabu-based one-to-one swap and the destroy and repair operators, are proposed to search the solution space from two perspectives, i.e., “adjustment” and “reconstruction.” To solve the problem effectively and efficiently, the former excludes certain agent-exchange combinations that do not improve the current solution, while the latter consists of multiple heuristic rules extracted from the correlation among different model elements. Experimental results have demonstrated that the proposed method surpasses several advanced methods across various scenarios regarding multiple factors, such as the number of agents, the number of missions, and the demand-supply ratio on capabilities.
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.