{"title":"多目标系统冗余分配问题的修剪Pareto集的确定","authors":"S. Kulturel-Konak, D. Coit","doi":"10.1109/MCDM.2007.369118","DOIUrl":null,"url":null,"abstract":"In this paper, a new methodology is presented to solve multi-objective system redundancy allocation problems. A tabu search meta-heuristic approach is used to initially find the entire Pareto set, and then a Monte-Carlo simulation provides a decision maker with a pruned set of Pareto solutions based on decision maker's predefined objective function preferences. We are aiming to create a bridge between Pareto optimality and single solution approaches","PeriodicalId":306422,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Determination of Pruned Pareto Sets for the Multi-Objective System Redundancy Allocation Problem\",\"authors\":\"S. Kulturel-Konak, D. Coit\",\"doi\":\"10.1109/MCDM.2007.369118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new methodology is presented to solve multi-objective system redundancy allocation problems. A tabu search meta-heuristic approach is used to initially find the entire Pareto set, and then a Monte-Carlo simulation provides a decision maker with a pruned set of Pareto solutions based on decision maker's predefined objective function preferences. We are aiming to create a bridge between Pareto optimality and single solution approaches\",\"PeriodicalId\":306422,\"journal\":{\"name\":\"2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MCDM.2007.369118\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCDM.2007.369118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determination of Pruned Pareto Sets for the Multi-Objective System Redundancy Allocation Problem
In this paper, a new methodology is presented to solve multi-objective system redundancy allocation problems. A tabu search meta-heuristic approach is used to initially find the entire Pareto set, and then a Monte-Carlo simulation provides a decision maker with a pruned set of Pareto solutions based on decision maker's predefined objective function preferences. We are aiming to create a bridge between Pareto optimality and single solution approaches
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