6_Decision_Analysis_(Student)

6_Decision_Analysis_(Student) - Decision Analysis (DA)...

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1 Decision Analysis (DA) Chapter 12 2 To learn the formulation of decision problems Decision Table (also refer to as Decision Matrix and Payoff Table) Decision Tree To learn the use of EMV (E xpected M onetary V alue) for decision making To understand the basic concepts of EVPI (E xpected V alue of P erfect I nformation) To review the conditional probabilities and Bayesian Theorem To discuss the use of additional information in a decision process To understand the basic concepts of EVSI (E xpected V alue of S ample I nformation) Chapter Outline 3 1. Formulate the problem Goals and objectives ( Maximization or Minimization ) Possible decision alternatives ( alternative courses of action ) Possible future outcomes ( states of nature ) and their probabilities Payoffs 2. Evaluate the alternatives Eliminate inadmissible alternative (no matter what the state of nature is, the payoff for inadmissible alternative is worse than the payoff for other alternatives) Compute the expected monetary value (expected payoffs / expected costs) for the admissible alternatives 3. Select the best alternative Select the alternative that maximize expected profits / minimize expected costs Decision Making Process (1 of 2) 4 Why is decision-making hard? Too many combinations of options to consider Consequence of our action (payoffs) depends on future events which are not known when decisions have to be made Decision Making Process (2 of 2)
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5 In the framework of decision analysis under uncertainty, decision maker has a finite number of alternatives (alternative courses of actions), there is a finite number of states of nature (future outcomes), with a corresponding probability for each state of nature, and for each alternative and state of nature combination, there is an associated payoff (usually of monetary value). Decision Making Under Uncertainty 6 Woke up at 8:45am! Have to be at work at 9:00am $1 penalty for each minute LATE What should I do? Bus? MTR? Taxi? What’s the traffic like? Example 1: City Slackers Problem Statement (1 of 2) 7 Uncertain traffic conditions (states of nature): Light traffic (40% chance) Busy traffic (60% chance) 3 modes of transport to choose (alternatives): Which transport mode should be chosen? Example 1: City Slackers Problem Statement (2 of 2) 30 45 Taxi (busy traffic) 10 35 Taxi (light traffic) 40 2.3 Bus (busy traffic) 15 2.3 Bus (light traffic) 25 9 MTR Travel Time (Mins) Cost ($) 8 1. Formulate the problem by a decision table: The cost decision table ( Minimization ) shows the payoff (cost in $) for each alternative under each state of nature Example 1: City Slackers Decision Making Process (1 of 4) 19 ($9 transport + $10 late) 19 ($9 transport + $10 late) MTR 60 ($45 transport + $15 late) 35 ($35 transport + $0 late) Taxi 27.3 ($2.3 transport + $25 late) 2.3 ($2.3 transport + $0 late) Bus Busy Traffic, 0.6 Light Traffic, 0.4 Alternative State of Nature
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6_Decision_Analysis_(Student) - Decision Analysis (DA)...

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