{"title":"利用模糊信息量集合还原帕累托集合的算法","authors":"V. D. Noghin","doi":"10.3103/s0147688223060126","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This paper deals with the multi-criteria problem of choice with a numerical vector function defined on a set of feasible variants. It is assumed that the decision maker uses a fuzzy preference relation for the choice process. Information on the preference relation is considered to be known in the form of a finite collection of fuzzy quanta. We formulate an algorithm to reduce the Pareto set in the multicriteria choice problem using the set of quanta in order to facilitate the final choice. A numerical example illustrates the operation of the algorithm.</p>","PeriodicalId":43962,"journal":{"name":"Scientific and Technical Information Processing","volume":"19 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Algorithm for the Reduction of the Pareto Set Using a Collection of Fuzzy Information Quanta\",\"authors\":\"V. D. Noghin\",\"doi\":\"10.3103/s0147688223060126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Abstract</h3><p>This paper deals with the multi-criteria problem of choice with a numerical vector function defined on a set of feasible variants. It is assumed that the decision maker uses a fuzzy preference relation for the choice process. Information on the preference relation is considered to be known in the form of a finite collection of fuzzy quanta. We formulate an algorithm to reduce the Pareto set in the multicriteria choice problem using the set of quanta in order to facilitate the final choice. A numerical example illustrates the operation of the algorithm.</p>\",\"PeriodicalId\":43962,\"journal\":{\"name\":\"Scientific and Technical Information Processing\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2024-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific and Technical Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3103/s0147688223060126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific and Technical Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3103/s0147688223060126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Algorithm for the Reduction of the Pareto Set Using a Collection of Fuzzy Information Quanta
Abstract
This paper deals with the multi-criteria problem of choice with a numerical vector function defined on a set of feasible variants. It is assumed that the decision maker uses a fuzzy preference relation for the choice process. Information on the preference relation is considered to be known in the form of a finite collection of fuzzy quanta. We formulate an algorithm to reduce the Pareto set in the multicriteria choice problem using the set of quanta in order to facilitate the final choice. A numerical example illustrates the operation of the algorithm.
期刊介绍:
Scientific and Technical Information Processing is a refereed journal that covers all aspects of management and use of information technology in libraries and archives, information centres, and the information industry in general. Emphasis is on practical applications of new technologies and techniques for information analysis and processing.