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Risk Analysis:Society for Risk Analysis Risk of Extreme Events in Multiobjective Decision Trees

论文作者:留学生论文论文属性:案例分析 Case Study登出时间:2011-01-31编辑:anterran点击率:20071

论文字数:4732论文编号:org201101311037533047语种:英语 English地区:澳大利亚价格:免费论文

附件:20110131103753310.pdf

关键词:Society for Risk AnalysisRisk of Extreme EventsMultiobjective Decision TreesDecision treemultiple objectivesextreme eventsconditional expected value

Risk Analysis,Vol.20,No.1,2000
125 0272-4332/00/0200-0125$16.00/1?2000

 Society for Risk Analysis Risk of Extreme Events in Multiobjective 代写留学生论文Decision Trees
Part 2.Rare Events
Hendrik I.Frohwein,1 Yacov Y.Haimes,2 and James H.Lambert1
Earlier work with decision trees identified nonseparability as an obstacle to minimizing theconditional expected value,a measure of the risk of extreme events,by the well-knownmethod of averaging out and folding back.This second of two companion papers addresses
the conditional expected value that is defined as the expected outcome assuming that a ran-dom variable is observed only in the upper 100(1)percent of potential outcomes,whereis a cumulative probability preselected by the decision maker.An approach is proposed to
overcome the need to evaluate all policies in order to identify the optimal policy.The ap-proach is based in part on approximating the conditional expected value by using statistics ofextremes.An existing convenient approximation of the conditional expected value is shown
to be separable into two constituent elements of risk and can thus be optimized,along withother objectives including the unconditional expected value of the outcome,in a multiobjec-tive decision tree.An example of sequential decision making for remediation or environmen-
tal contamination is provided.The importance of the results for risk analyis beyond the min-imization of conditional expected values is pointed out.
KEY WORDS:Decision tree;multiple objectives;extreme events;conditional expected value
1.INTRODUCTION
This is the second of two companion papers onthe averaging out and folding back of measures ofrisk of extreme events in decision trees.Decisiontrees have found widespread attention in literatureand practice,but their use has commonly been re-stricted to the optimization of a single objective.Haimes et al.(1990)have introduced the concept ofmultiobjective decision trees(MODT).However,they identified a difficulty with the averaging out andfolding back of conditional expected values of theoutcome,a measure of the risk of extreme events.Thepresent paper and its companion in this issue(Froh-wein et al.2000)are devoted to developing methodsto overcome this obstacle.
Frohwein and Lambert(2000)promulgate theuse of some measure of the risk of extreme events indecision analysis as a complement to the unconditionalexpected value of the outcome and review MODTs.Whereas the first paper deals with the use of theconditional expected value of the outcome(a loss ordamage),given that the magnitude of the outcome ex-ceeds a given threshold(severe events),this paperinvestigates an alternative measure of the risk of ex-treme events.This measure is the conditional expectedvalue of the outcome,given that the magnitude of the
outcome falls in the upper 100(1)percent tail of thecumulative probability distribution of outcomes.Thisdefines,on the basis ofcumulative probability,arange of rare events that are known to be of concern tothe decision maker.This type of conditional expectedvalue can also be interpreted as the“worst 100(1)-Center for Risk Management of Engineering Systems,Universityof Virginia,Charlottesville,VA.Center for Risk Management of Engineering Systems,104 Olsson
Hall,University of Virginia,Charlottesville,VA 22903.126 Frohwein et al.
in-100 expectation.”Calculating conditional expected
values on the basis of a fixed probability may be lessintuitive than calculat论文英语论文网提供整理,提供论文代写英语论文代写代写论文代写英语论文代写留学生论文代写英文论文留学生论文代写相关核心关键词搜索。

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