{"title":"Imprecise covering ring star problem","authors":"","doi":"10.31181/dmame0323062022s","DOIUrl":null,"url":null,"abstract":"In this paper, we formulate and solve an Imprecise Covering Ring Star Problem (ICRSP), which is a generalization of the Ring Star Problem (RSP). Here the objective of this problem is to find a subset of nodes in a network to minimize the sum of routing costs of interconnecting cycle and assignment costs of the nodes which are out of cycle, to their nearest concentrators such that no assigned node exceeds a predetermined distance (say, covering distance) from the concentrators. The covering distance, as well as the routing and assignments costs, are considered as fuzzy in the proposed ICRSP. A Modified Genetic Algorithm (MGA) is developed and used to solve this model for different confidence levels depending on the corresponding imprecise parameters, reducing it to deterministic form with fuzzy possibility and necessity approaches. Some comparisons with existing benchmark problems are made to justify the performance of the algorithm. As individual cases, some practical ICRSPs are also solved and presented numerically.","PeriodicalId":32695,"journal":{"name":"Decision Making Applications in Management and Engineering","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Making Applications in Management and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31181/dmame0323062022s","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Decision Sciences","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we formulate and solve an Imprecise Covering Ring Star Problem (ICRSP), which is a generalization of the Ring Star Problem (RSP). Here the objective of this problem is to find a subset of nodes in a network to minimize the sum of routing costs of interconnecting cycle and assignment costs of the nodes which are out of cycle, to their nearest concentrators such that no assigned node exceeds a predetermined distance (say, covering distance) from the concentrators. The covering distance, as well as the routing and assignments costs, are considered as fuzzy in the proposed ICRSP. A Modified Genetic Algorithm (MGA) is developed and used to solve this model for different confidence levels depending on the corresponding imprecise parameters, reducing it to deterministic form with fuzzy possibility and necessity approaches. Some comparisons with existing benchmark problems are made to justify the performance of the algorithm. As individual cases, some practical ICRSPs are also solved and presented numerically.