Lecture 16 CEE 270
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This 2 page Class Notes was uploaded by Nathaniel Bautz on Monday March 30, 2015. The Class Notes belongs to CEE 270 at University of Massachusetts taught by Bernd Schliemann in Spring2015. Since its upload, it has received 54 views. For similar materials see System Analysis and Economic Civil Engineering in Civil and Environmental Engineering at University of Massachusetts.
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Date Created: 03/30/15
CHAPTER 16 DECISION ANALYSIS 0 90 O 90 O 90 O 90 O 90 Chapter 16 Concepts gt Sensitivity Analysis gt Decision Making under Risk Certainty Risk Uncertainty gt In engineering economy we deal with the future I Future cash ows I Future interest rates gt Certainty Everything is known for sure I The cash ow will be 1000 gt Risk All possible outcomes and probabilities are known gt Uncertainty Probabilities of outcomes are unknown Sensitivity Analysis gt Calculate how sensitive your results are to variations in your data gt To date we ve mostly assumed our estimates are correct Parameters gt A parameter is a variable or factor for which an estimate is needed I Examples 0 P F A I i n 0 Future costs salvages etc Types of Decision Making gt Decision making under certainty I No guarantee of best decision inputs vary gt Decision making under risk I Inputs are viewed as uncertain and element of chance is considered I Variation is present and must be accounted for Probabilities are assigned or estimated I Involves the notation of random variables gt Decision Making under Pure Uncertainty I Unknown probabilities gt Decision making under turbulence I The worst possible outcomes and their probabilities unknown Decision Making Under Risk gt Discrete variable or Continuous variable I Discrete variable specific set of possible values I Continuous variable infinite number of possible values Stages Evaluation of Alternatives gt Some problems involve stages decisions that occur in sequence gt Define the staged decisions and assign respective probabilities to outcomes gt Useful tool Decision trees gt The objective Make risk more explicit Decision Tree gt Visually display the problem gt Organize the calculations gt Elements I Decision node I Event chance or probability node I Terminal branch gt A sequence of decisions Solving Decision Trees gt Define all of the decision points gt Define the outcomes gt Assign probabilities to mutually exclusive outcomes emanating from each decision node I These probabilities sum to 1 for each set of outcomes branches that are possible from a given decision
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