{"title":"一种用于网络可靠性分析的敌对模型","authors":"Dan Lena, F. Robledo, P. Romero","doi":"10.17535/CRORR.2017.0031","DOIUrl":null,"url":null,"abstract":"In reliability analysis, the goal is to determine the probability of consistentoperation of a system. We introduce the Hostile model, where the system under study is a network, and all the components may fail (both sites and links), except for a distinguished subset of sites, called terminals. The Hostile model includes the Classical Reliability model as a particular case. As a corollary, the exact reliability evaluation of a network in the Hostile model belongs to the list of NP-hard computational problems. Traditional methods for the classical reliability model such as Crude Monte Carlo, Importance Sampling and Recursive Variance Reduction are here adapted for the Hostile model. The performance of these methods is finally discussed using real-life networks.","PeriodicalId":44065,"journal":{"name":"Croatian Operational Research Review","volume":"8 1","pages":"489-498"},"PeriodicalIF":0.4000,"publicationDate":"2017-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.17535/CRORR.2017.0031","citationCount":"6","resultStr":"{\"title\":\"A Hostile model for network reliability analysis\",\"authors\":\"Dan Lena, F. Robledo, P. Romero\",\"doi\":\"10.17535/CRORR.2017.0031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In reliability analysis, the goal is to determine the probability of consistentoperation of a system. We introduce the Hostile model, where the system under study is a network, and all the components may fail (both sites and links), except for a distinguished subset of sites, called terminals. The Hostile model includes the Classical Reliability model as a particular case. As a corollary, the exact reliability evaluation of a network in the Hostile model belongs to the list of NP-hard computational problems. Traditional methods for the classical reliability model such as Crude Monte Carlo, Importance Sampling and Recursive Variance Reduction are here adapted for the Hostile model. The performance of these methods is finally discussed using real-life networks.\",\"PeriodicalId\":44065,\"journal\":{\"name\":\"Croatian Operational Research Review\",\"volume\":\"8 1\",\"pages\":\"489-498\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2017-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.17535/CRORR.2017.0031\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Croatian Operational Research Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17535/CRORR.2017.0031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Croatian Operational Research Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17535/CRORR.2017.0031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
In reliability analysis, the goal is to determine the probability of consistentoperation of a system. We introduce the Hostile model, where the system under study is a network, and all the components may fail (both sites and links), except for a distinguished subset of sites, called terminals. The Hostile model includes the Classical Reliability model as a particular case. As a corollary, the exact reliability evaluation of a network in the Hostile model belongs to the list of NP-hard computational problems. Traditional methods for the classical reliability model such as Crude Monte Carlo, Importance Sampling and Recursive Variance Reduction are here adapted for the Hostile model. The performance of these methods is finally discussed using real-life networks.
期刊介绍:
Croatian Operational Research Review (CRORR) is the journal which publishes original scientific papers from the area of operational research. The purpose is to publish papers from various aspects of operational research (OR) with the aim of presenting scientific ideas that will contribute both to theoretical development and practical application of OR. The scope of the journal covers the following subject areas: linear and non-linear programming, integer programing, combinatorial and discrete optimization, multi-objective programming, stohastic models and optimization, scheduling, macroeconomics, economic theory, game theory, statistics and econometrics, marketing and data analysis, information and decision support systems, banking, finance, insurance, environment, energy, health, neural networks and fuzzy systems, control theory, simulation, practical OR and applications. The audience includes both researchers and practitioners from the area of operations research, applied mathematics, statistics, econometrics, intelligent methods, simulation, and other areas included in the above list of topics. The journal has an international board of editors, consisting of more than 30 editors – university professors from Croatia, Slovenia, USA, Italy, Germany, Austria and other coutries.