{"title":"有限预算共识与最大共识水平的群体决策","authors":"Huanhuan Zhang , Dongjie Guo , Yifeng Ma","doi":"10.1016/j.asoc.2025.113905","DOIUrl":null,"url":null,"abstract":"<div><div>Group decision making usually requires in-depth discussions to form a consensus acceptable to the entire group, which has attracted more and more research in recent years. Despite extensive studies on soft consensus, the relationship between consensus level and consensus cost remains unclear. This study establishes—for the first time—a precise mathematical relationship demonstrating that higher consensus levels require proportionally greater consensus costs. This finding provides critical theoretical grounding for consensus modeling. Recognizing that the cost of achieving consensus cannot be infinite and must be within a certain budget, we develop a model to determine the maximum achievable consensus level under a limited-budget. The consensus model with non-cooperators is also explored and formulated. The proposed models are applied to online lending platforms, providing a practical framework for measuring consensus levels and achieving soft consensus between lenders and borrowers within a limited-budget. This work contributes to understanding the relationship between consensus level and consensus cost, as well as the achievement of the maximum possible consensus level under limited-budget, which is relevant in scenarios where resources are finite.</div></div>","PeriodicalId":50737,"journal":{"name":"Applied Soft Computing","volume":"185 ","pages":"Article 113905"},"PeriodicalIF":6.6000,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Limited-budget consensus with maximum consensus level for group decision making\",\"authors\":\"Huanhuan Zhang , Dongjie Guo , Yifeng Ma\",\"doi\":\"10.1016/j.asoc.2025.113905\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Group decision making usually requires in-depth discussions to form a consensus acceptable to the entire group, which has attracted more and more research in recent years. Despite extensive studies on soft consensus, the relationship between consensus level and consensus cost remains unclear. This study establishes—for the first time—a precise mathematical relationship demonstrating that higher consensus levels require proportionally greater consensus costs. This finding provides critical theoretical grounding for consensus modeling. Recognizing that the cost of achieving consensus cannot be infinite and must be within a certain budget, we develop a model to determine the maximum achievable consensus level under a limited-budget. The consensus model with non-cooperators is also explored and formulated. The proposed models are applied to online lending platforms, providing a practical framework for measuring consensus levels and achieving soft consensus between lenders and borrowers within a limited-budget. This work contributes to understanding the relationship between consensus level and consensus cost, as well as the achievement of the maximum possible consensus level under limited-budget, which is relevant in scenarios where resources are finite.</div></div>\",\"PeriodicalId\":50737,\"journal\":{\"name\":\"Applied Soft Computing\",\"volume\":\"185 \",\"pages\":\"Article 113905\"},\"PeriodicalIF\":6.6000,\"publicationDate\":\"2025-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Soft Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1568494625012189\",\"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":"Applied Soft Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1568494625012189","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}
Limited-budget consensus with maximum consensus level for group decision making
Group decision making usually requires in-depth discussions to form a consensus acceptable to the entire group, which has attracted more and more research in recent years. Despite extensive studies on soft consensus, the relationship between consensus level and consensus cost remains unclear. This study establishes—for the first time—a precise mathematical relationship demonstrating that higher consensus levels require proportionally greater consensus costs. This finding provides critical theoretical grounding for consensus modeling. Recognizing that the cost of achieving consensus cannot be infinite and must be within a certain budget, we develop a model to determine the maximum achievable consensus level under a limited-budget. The consensus model with non-cooperators is also explored and formulated. The proposed models are applied to online lending platforms, providing a practical framework for measuring consensus levels and achieving soft consensus between lenders and borrowers within a limited-budget. This work contributes to understanding the relationship between consensus level and consensus cost, as well as the achievement of the maximum possible consensus level under limited-budget, which is relevant in scenarios where resources are finite.
期刊介绍:
Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities.
Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.