5S Decision Theory McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc All Learning Objectives Describe the different environments under which operations decisions are made Describe and use techniques that apply decision making theory under uncertainty Describe and use the expected-value approach 5S-2 Learning Objectives Construct a decision tree and use it to analyze a problem Compute the expected value of perfect information Conduct sensitivity analysis on a simple decision problem 5S-3 Decision Theory Decision Theory represents a general approach to decision making which is suitable for a wide range of operations management decisions, including: Capacity planning Location planning Product Product and and service service design design Equipment selection 5S-4 Decision Theory Elements A set of possible future conditions exists that will have a bearing on the results of the decision A list of alternatives for the manager to choose from A known payoff for each alternative under each possible future condition 5S-5 Decision Theory Process Identify possible future conditions called states of nature Develop a list of possible alternatives, one of which may be to nothing Determine the payoff associated with each alternative for every future condition 5S-6 Decision Theory Process (Cont’d) If possible, determine the likelihood of each possible future condition Evaluate alternatives according to some decision criterion and select the best alternative 5S-7 Causes of Poor Decisions Bounded Rationality The limitations on decision making caused by costs, human abilities, time, technology, and availability of information 5S-8 Causes of Poor Decisions (Cont’d) Suboptimization The result of different departments each attempting to reach a solution that is optimum for that department 5S-9 Decision Process Identify the problem Specify objectives and criteria for a solution Develop suitable alternatives Analyze and compare alternatives Select the best alternative Implement the solution Monitor to see that the desired result is achieved 5S-10 Decision Environments Certainty - Environment in which relevant parameters have known values Risk - Environment in which certain future events have probable outcomes Uncertainty - Environment in which it is impossible to assess the likelihood of various future events 5S-11 Decision Making under Uncertainty Maximin - Choose the alternative with the best of the worst possible payoffs Maximax - Choose the alternative with the best possible payoff Laplace - Choose the alternative with the best average payoff of any of the alternatives Minimax Regret - Choose the alternative that has the least of the worst regrets 5S-12 Decision Making Under Risk Risk: The probability of occurrence for each state of nature is known Risk lies between the extremes of uncertainty and certainty Expected monetary value (EMV) criterion: The best expected value among alternatives Determine the expected payoff of each alternative, and choose the alternative with the best expected payoff 5S-13 Decision Trees Decision tree: a Schematic representation of the available alternatives and their possible consequences Useful for analyzing situations that involve sequential decisions See Figure 5S.1 5S-14 Format of a Decision Tree Figure 5S.1 Decision Point Chance Event A’ e s o o h C S t at e State tu r e a n f o of nat C ho os St e r u t f na o e t a Payoff Choose A’2 Payoff A’ Payoff A’4 Payoff e Ch oo s Choose e A’ State A’ e s o o Ch ure B Payoff of nat ure Payoff 5S-15 Expected Value of Perfect Information Expected value of perfect information: the difference between the expected payoff under certainty and the expected payoff under risk Expected value of Expected payoff perfect information = under certainty - Expected payoff under risk 5S-16 Sensitivity Analysis Sensitivity Analysis: Determining the range of probability for which an alternative has the best expected payoff Useful for decision makers to have some indication of how sensitive the choice of an alternative is to changes in one or more of these values 5S-17 Sensitivity Analysis Example S-8 #1 Payoff 16 14 12 10 #2 Payoff B C B best C best A A best Sensitivity analysis: determine the range of probability for which an alternative has the best expected payoff 5S-18 16 14 12 10 Solved Problem 5S-19 ... Theory represents a general approach to decision making which is suitable for a wide range of operations management decisions, including: Capacity planning Location planning Product Product and and...Learning Objectives Describe the different environments under which operations decisions are made Describe and use techniques that apply decision making theory under... alternative 5S-7 Causes of Poor Decisions Bounded Rationality The limitations on decision making caused by costs, human abilities, time, technology, and availability of information 5S-8 Causes of Poor