{"title":"基于互动迭代共识的社会网络大规模群体决策方法及其在零废弃物城市评估中的应用","authors":"Fanyong Meng , Hao Li , Jinyu Li","doi":"10.1016/j.inffus.2024.102744","DOIUrl":null,"url":null,"abstract":"<div><div>The construction of zero-waste (ZW) cities receives increasing attention from the Chinese government. The evaluation is essential to make policy variations according to the actual situation in each place. Previous assessments of ZW cities have primarily relied on historical data, which fails to account for the subjective preferences of various stakeholders. For example, it is challenging to capture residents' subjective opinions about the development of a ZW city. This paper presents a social network large-scale group decision-making method for evaluating the construction of ZW city. First, experts' evaluation opinions and trust relations are used to develop an improved clustering method. The weights of the clusters are then determined using internal-external cohesion indices and the number of experts, with experts' weights defined by their similarity-trust degree. An optimization model based on interactive iteration consensus is formulated, considering the fairness and rationality of allocation schemes. Additionally, a new social network large-scale group decision-making method is presented. Finally, the proposed method is illustrated with a case study of selecting a national-level ZW city in Jiangsu Province.</div></div>","PeriodicalId":50367,"journal":{"name":"Information Fusion","volume":"115 ","pages":"Article 102744"},"PeriodicalIF":14.7000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An interactive iteration consensus based social network large-scale group decision making method and its application in zero-waste city evaluation\",\"authors\":\"Fanyong Meng , Hao Li , Jinyu Li\",\"doi\":\"10.1016/j.inffus.2024.102744\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The construction of zero-waste (ZW) cities receives increasing attention from the Chinese government. The evaluation is essential to make policy variations according to the actual situation in each place. Previous assessments of ZW cities have primarily relied on historical data, which fails to account for the subjective preferences of various stakeholders. For example, it is challenging to capture residents' subjective opinions about the development of a ZW city. This paper presents a social network large-scale group decision-making method for evaluating the construction of ZW city. First, experts' evaluation opinions and trust relations are used to develop an improved clustering method. The weights of the clusters are then determined using internal-external cohesion indices and the number of experts, with experts' weights defined by their similarity-trust degree. An optimization model based on interactive iteration consensus is formulated, considering the fairness and rationality of allocation schemes. Additionally, a new social network large-scale group decision-making method is presented. Finally, the proposed method is illustrated with a case study of selecting a national-level ZW city in Jiangsu Province.</div></div>\",\"PeriodicalId\":50367,\"journal\":{\"name\":\"Information Fusion\",\"volume\":\"115 \",\"pages\":\"Article 102744\"},\"PeriodicalIF\":14.7000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Fusion\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1566253524005220\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Fusion","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1566253524005220","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
An interactive iteration consensus based social network large-scale group decision making method and its application in zero-waste city evaluation
The construction of zero-waste (ZW) cities receives increasing attention from the Chinese government. The evaluation is essential to make policy variations according to the actual situation in each place. Previous assessments of ZW cities have primarily relied on historical data, which fails to account for the subjective preferences of various stakeholders. For example, it is challenging to capture residents' subjective opinions about the development of a ZW city. This paper presents a social network large-scale group decision-making method for evaluating the construction of ZW city. First, experts' evaluation opinions and trust relations are used to develop an improved clustering method. The weights of the clusters are then determined using internal-external cohesion indices and the number of experts, with experts' weights defined by their similarity-trust degree. An optimization model based on interactive iteration consensus is formulated, considering the fairness and rationality of allocation schemes. Additionally, a new social network large-scale group decision-making method is presented. Finally, the proposed method is illustrated with a case study of selecting a national-level ZW city in Jiangsu Province.
期刊介绍:
Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.