To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Supplement S2 Decision Analysis To.

Slides:

Advertisements

Similar presentations

Decision Theory.

Advertisements

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-1 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Prepared by.

Chapter 3 Decision Analysis.

Decision Analysis Chapter 3

1 Decision Analysis What is it? What is the objective? More example Tutorial: 8 th ed:: 5, 18, 26, 37 9 th ed: 3, 12, 17, 24 (to p2) (to p5) (to p50)

12-1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Decision Analysis Chapter 12.

Chapter 14 Decision Analysis. Decision Making Many decision making occur under condition of uncertainty Decision situations –Probability cannot be assigned.

Introduction to Management Science

McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 5S Decision Theory.

Introduction to Management Science

Decision Theory.

Decision Process Identify the Problem

LECTURE TWELVE Decision-Making UNDER UNCERTAINITY.

Copyright 2009 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Operations Management - 6 th Edition Chapter 1 Supplement Roberta.

1 DSCI 3223 Decision Analysis Decision Making Under Uncertainty –Techniques play an important role in business, government, everyday life, college football.

Chapter 3 Decision Analysis.

Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter Twenty An Introduction to Decision Making GOALS.

Decision Analysis. What is Decision Analysis? The process of arriving at an optimal strategy given: –Multiple decision alternatives –Uncertain future.

Managerial Decision Modeling with Spreadsheets

2000 by Prentice-Hall, Inc1 Supplement 2 – Decision Analysis A set of quantitative decision-making techniques for decision situations where uncertainty.

Operations and Supply Chain Management, 8th Edition

3 Decision Analysis To accompany Quantitative Analysis for Management, Twelfth Edition, by Render, Stair, Hanna and Hale Power Point slides created by.

Decision Analysis Chapter 12.

Decision Theory is a body of knowledge and related analytical techniques Decision is an action to be taken by the Decision Maker Decision maker is a person,

Part 3 Probabilistic Decision Models

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 18-1 Business Statistics: A Decision-Making Approach 6 th Edition Chapter.

DECISION THEORY Decision theory is an analytical and systematic way to tackle problems A good decision is based on logic.

5s-1Decision Theory McGraw-Hill/Irwin Operations Management, Eighth Edition, by William J. Stevenson Copyright © 2005 by The McGraw-Hill Companies, Inc.

Copyright 2006 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Operations Management - 5 th Edition Chapter 2 Supplement Roberta.

Decision Analysis Chapter 3

Decision Making Under Uncertainty and Under Risk

Decision analysis: part 1 BSAD 30 Dave Novak Source: Anderson et al., 2013 Quantitative Methods for Business 12 th edition – some slides are directly from.

Chapter 1 Supplement Decision Analysis Supplement 1-1.

Decision Tree Analysis. Decision Analysis Managers often must make decisions in environments that are fraught with uncertainty. Some Examples –A manufacturer.

Decision Analysis Introduction Chapter 6. What kinds of problems ? Decision Alternatives (“what ifs”) are known States of Nature and their probabilities.

Operations Management Decision-Making Tools Module A

5s-1 McGraw-Hill Ryerson Operations Management, 2 nd Canadian Edition, by Stevenson & Hojati Copyright © 2004 by The McGraw-Hill Companies, Inc. All rights.

Operations Management Decision-Making Tools Module A

Operational Decision-Making Tools: Decision Analysis

CD-ROM Chap 14-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In Business Statistics 4 th Edition CD-ROM Chapter 14 Introduction.

Decision Analysis Chapter 3

PowerPoint presentation to accompany Operations Management, 6E (Heizer & Render) © 2001 by Prentice Hall, Inc., Upper Saddle River, N.J A-1 Operations.

OPIM 204: Lecture #1 Introduction to OM OPIM 204 Operations Management Instructor: Jose M. Cruz Office: Room 332 Phone: (203)

Decision Theory Decision theory problems are characterized by the following: 1.A list of alternatives. 2.A list of possible future states of nature. 3.Payoffs.

1 1 Slide Decision Theory Professor Ahmadi. 2 2 Slide Learning Objectives n Structuring the decision problem and decision trees n Types of decision making.

12-1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Decision Analysis Chapter 12.

Operations Research II Course,, September Part 5: Decision Models Operations Research II Dr. Aref Rashad.

Copyright 2006 John Wiley & Sons, Inc. OPIM 3104: Lecture #1 Introduction to OM Instructor: Jose M. Cruz.

Welcome Unit 4 Seminar MM305 Wednesday 8:00 PM ET Quantitative Analysis for Management Delfina Isaac.

Decision Theory McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

Models for Strategic Marketing Decision Making. Market Entry Decisions To enter first or to wait Sources of First-Mover Advantages –Technological leadership.

Decision Theory McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

12-1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Decision Analysis Chapter 12.

Decision Analysis.

SUPPLEMENT TO CHAPTER TWO Irwin/McGraw-Hill © The McGraw-Hill Companies, Inc., 1999 DECISION MAKING 2S-1 Chapter 2 Supplement Decision Making.

Decision Making Under Uncertainty: Pay Off Table and Decision Tree.

Decision Theory Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill.

Chapter 12 Decision Analysis. Components of Decision Making (D.M.) F Decision alternatives - for managers to choose from. F States of nature - that may.

DECISION MODELS. Decision models The types of decision models: – Decision making under certainty The future state of nature is assumed known. – Decision.

Chap 18-1 Business Statistics: A Decision-Making Approach 6 th Edition Chapter 18 Introduction to Decision Analysis.

QUANTITATIVE TECHNIQUES

McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 4 Decision Analysis Building the Structure for Solving.

DECISION THEORY & DECISION TREE

Decision Analysis Chapter 12.

OPERATIONS MANAGEMENT: Creating Value Along the Supply Chain,

Chapter 19 Decision Making

Decision Analysis Chapter 12.

MNG221- Management Science –

Decision Analysis Support Tools and Processes

Presentation transcript:

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Supplement S2 Decision Analysis To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved.

Decision Analysis A set of quantitative decision- making techniques for decision situations where uncertainty exists A set of quantitative decision- making techniques for decision situations where uncertainty exists

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Making States of nature States of nature Events that may occur in the future Events that may occur in the future Decision maker is uncertain which state of nature will occur Decision maker is uncertain which state of nature will occur Decision maker has no control over the states of nature Decision maker has no control over the states of nature

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Payoff Table A method of organizing & illustrating the payoffs from different decisions given various states of nature A method of organizing & illustrating the payoffs from different decisions given various states of nature A payoff is the outcome of the decision A payoff is the outcome of the decision

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Payoff Table States Of Nature Decisionab 1Payoff 1aPayoff 1b 2Payoff 2aPayoff 2b Table S2.1

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Making Criteria Under Uncertainty Maximax criterion Maximax criterion Choose decision with the maximum of the maximum payoffs Choose decision with the maximum of the maximum payoffs Maximin criterion Maximin criterion Choose decision with the maximum of the minimum payoffs Choose decision with the maximum of the minimum payoffs Minimax regret criterion Minimax regret criterion Choose decision with the minimum of the maximum regrets for each alternative Choose decision with the minimum of the maximum regrets for each alternative

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Hurwicz criterion Hurwicz criterion Choose decision in which decision payoffs are weighted by a coefficient of optimism,  Choose decision in which decision payoffs are weighted by a coefficient of optimism,  Coefficient of optimism (  ) is a measure of a decision maker’s optimism, from 0 (completely pessimistic) to 1 (completely optimistic) Coefficient of optimism (  ) is a measure of a decision maker’s optimism, from 0 (completely pessimistic) to 1 (completely optimistic) Equal likelihood (La Place) criterion Equal likelihood (La Place) criterion Choose decision in which each state of nature is weighted equally Choose decision in which each state of nature is weighted equally

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Company STATES OF NATURE Good ForeignPoor Foreign DECISION Competitive ConditionsCompetitive Conditions Expand$ 800,000$ 500,000 Maintain status quo1,300, ,000 Sell now320,000320,000 Example S2.1

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Company STATES OF NATURE Good ForeignPoor Foreign DECISION Competitive ConditionsCompetitive Conditions Expand$ 800,000$ 500,000 Maintain status quo1,300, ,000 Sell now320,000320,000 Example S2.1 Maximax Solution Expand:$800,000 Status quo:1,300,000  Maximum Sell: 320,000 Decision: Maintain status quo

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Company STATES OF NATURE Good ForeignPoor Foreign DECISION Competitive ConditionsCompetitive Conditions Expand$ 800,000$ 500,000 Maintain status quo1,300, ,000 Sell now320,000320,000 Example S2.1 Maximin Solution Expand:$500,000  Maximum Status quo:-150,000 Sell: 320,000 Decision: Expand

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Company STATES OF NATURE Good ForeignPoor Foreign DECISION Competitive ConditionsCompetitive Conditions Expand$ 800,000$ 500,000 Maintain status quo1,300, ,000 Sell now320,000320,000 Example S2.1 Minimax Regret Solution $1,300, ,000= 500,000 $500, ,000= 0 1,300, ,300,000= 0500,000 - (-150,000)= 650,000 1,300, ,000= 980,000500, ,000= 180,000 GOOD CONDITIONSPOOR CONDITIONS Expand:$500,000  Minimum Status quo:650,000 Sell: 980,000 Decision: Expand

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Company STATES OF NATURE Good ForeignPoor Foreign DECISION Competitive ConditionsCompetitive Conditions Expand$ 800,000$ 500,000 Maintain status quo1,300, ,000 Sell now320,000320,000 Example S2.1 Hurwicz Criteria  =  = 0.7 Expand: $800,000(0.3) + 500,000(0.7) = $590,000  Maximum Status quo: 1,300,000(0.3) -150,000(0.7) = 285,000 Sell: 320,000(0.3) + 320,000(0.7) = 320,000 Decision: Expand

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Company STATES OF NATURE Good ForeignPoor Foreign DECISION Competitive ConditionsCompetitive Conditions Expand$ 800,000$ 500,000 Maintain status quo1,300, ,000 Sell now320,000320,000 Example S2.1 Equal Likelihood Criteria Two states of nature each weighted 0.50 Expand: $800,000(0.5) + 500,000(0.5) = $650,000  Maximum Status quo: 1,300,000(0.5) -150,000(0.5) = 575,000 Sell: 320,000(0.5) + 320,000(0.5) = 320,000 Decision: Expand

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Making with Probabilities Risk involves assigning probabilities to states of nature Risk involves assigning probabilities to states of nature Expected value is a weighted average of decision outcomes in which each future state of nature is assigned a probability of occurrence Expected value is a weighted average of decision outcomes in which each future state of nature is assigned a probability of occurrence

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Expected Value EV ( x ) = p ( x i ) x i n i =1 where x i = outcome i p ( x i )= probability of outcome i

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Company STATES OF NATURE Good ForeignPoor Foreign DECISION Competitive ConditionsCompetitive Conditions Expand$ 800,000$ 500,000 Maintain status quo1,300, ,000 Sell now320,000320,000 Example S2.2 Expected Value p (good) = 0.70 p (poor) = 0.30 EV(expand) $800,000(0.7) + 500,000(0.3) = $710,000 EV(status quo) 1,300,000(0.7) -150,000(0.3) = 865,000  Maximum EV(sell) 320,000(0.7) + 320,000(0.3) = 320,000 Decision: Status quo

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Expected Value of Perfect Information The maximum value of perfect information to the decision maker The maximum value of perfect information to the decision maker EVPI = (expected value given perfect information) - (expected value without perfect information) EVPI = (expected value given perfect information) - (expected value without perfect information)

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. EVPI Example Good conditions will exist 70% of the time, choose maintain status quo with payoff of $1,300,000 Good conditions will exist 70% of the time, choose maintain status quo with payoff of $1,300,000 Poor conditions will exist 30% of the time, choose expand with payoff of $500,000 Poor conditions will exist 30% of the time, choose expand with payoff of $500,000 Expected value given perfect information = $1,300,000 (0.70) + 500,000 (0.30) = $1,060,000 EVPI= $1,060, ,000 = $195,000 Expected value given perfect information = $1,300,000 (0.70) + 500,000 (0.30) = $1,060,000 EVPI= $1,060, ,000 = $195,000

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Sequential Decision Trees A graphical method for analyzing decision situations that require a sequence of decisions over time A graphical method for analyzing decision situations that require a sequence of decisions over time Decision tree consists of Decision tree consists of Square nodes - indicating decision points Square nodes - indicating decision points Circles nodes - indicating states of nature Circles nodes - indicating states of nature Arcs - connecting nodes Arcs - connecting nodes

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Decision Tree Example S2.3

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Southern Textile Decision Tree Warehouse(-$600,000) Sell land Marketgrowth 0.70 Marketgrowth Expand(-$800,000) Purchase Land (-$200,000) Expand(-$800,000) No market growth $225,000 Market growth $2,000,000$3,000,000 $700,000 $2,300,000 $1,000,000 $210,000 No market growth growth 0.30 growth (3 years, $0 payoff) Market growth (3 years, $0 payoff) Example S2.3

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Evaluations at Nodes Compute EV at nodes 6 & 7 EV(node 6)= 0.80($3,000,000) ($700,000) = $2,540,000 EV(node 7)= 0.30($2,300,000) ($1,000,000) = $1,390,000 Expected values written above nodes 6 & 7 Decision at node 4 is between $2,540,000 for Expand and $450,000 for Sell land Choose Expand Repeat expected value calculations and decisions at remaining nodes

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Tree Solution Expand(-$800,000) Purchase Land (-$200,000) Expand(-$800,000) Warehouse(-$600,000) No market growth $225,000 Market growth $2,000,000$3,000,000 $700,000 $2,300,000 $1,000,000 $210,000 Marketgrowth Marketgrowth No market growth growth Sell land No market growth (3 years, $0 payoff) Market growth (3 years, $0 payoff) Example S2.3

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Tree Solution Expand(-$800,000) Purchase Land (-$200,000) $1,160,000 $1,360,000 $790,000 $1,390,000 $1,740,000 $2,540,000 Expand(-$800,000) Warehouse(-$600,000) No market growth $225,000 Market growth $2,000,000$3,000,000 $700,000 $2,300,000 $1,000,000 $210,000 Marketgrowth Marketgrowth No market growth growth Sell land No market growth (3 years, $0 payoff) Market growth (3 years, $0 payoff) $1,290, Example S2.3

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Analysis Exhibit S2.1

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Analysis Exhibit S2.2

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Analysis Exhibit S2.3 Formula for expected value computed in cell D6

To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Decision Analysis Exhibit S2.4 Enter problem parameters in cells B8:C11. Click on “OM” to access Decision Table macro.