Publication | Closed Access
Stochastic Ranking of Alternatives with Ordered Weighted Averaging: Comparing Network Recovery Strategies
10
Citations
21
References
2016
Year
Ranking AlgorithmEngineeringLearning To RankNetwork AnalysisDecision AnalysisRisk AnalysisImportance WeightingMultiple-criteria Decision AnalysisFuzzy Risk AnalysisDecision AnalyticsOperations ResearchFuzzy Multi-criteria Decision-makingData ScienceRisk ManagementManagementSystems EngineeringCombinatorial OptimizationDecision TheoryStatisticsWeighted AveragingQuantitative ManagementSocial Network AnalysisReliabilityRisk AnalyticsStochastic RankingSocial RankingPreference AggregationWeighted Owa ExtensionInteger ProgrammingNetwork ScienceNetwork AlgorithmDecision Science
ABSTRACT Comparing system design alternatives can be difficult when the criterion used to evaluate and rank the alternatives exhibits randomness described by a probability distribution. Rather than relying on the expected value to compare alternatives, this work proposes to use a multicriteria decision‐making technique, ordered weighted averaging (OWA), for such a comparison. Here, percentiles of the cumulative distributions describing the evaluation criterion act as the “multiple criteria” in OWA, incorporating information from the entirety of the distribution, not just a lone point estimate. OWA allows for the elicitation of risk preferences by the decision maker, and a weighted OWA extension allows for the elicitation of importance weighting for each of the percentiles (e.g., weighting tail values of the distribution more heavily to account for adverse outcomes). The technique is applied to the comparison of link recovery sequences in a network disruption problem, along with a visualization aid to assist in accounting for uncertainty in importance weighting.
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