Strategic Approach in Multi-Criteria Decision Making: A Practical Guide for Complex Scenarios (International Series in Operations Research & Management Science, 351)

✍ Scribed by Nolberto Munier

• Publisher: Springer
• Year: 2024
• Tongue: English
• Leaves: 407
• Edition: 2nd ed. 2024
• Category: Library

✦ Synopsis

This book examines multiple criteria decision making (MCDM) and presents the Sequential Iterative Modelling for Urban Systems (SIMUS) as a method to be used for strategic decision making. It emphasizes the necessity to take into account aspects related to real world scenarios and incorporating possible real-life aspects for modelling. The book also highlights the use of sensitivity analysis and presents a method for using criteria marginal values instead of weights, which permits the drawing of curves that depicts the variations of the objective function due to increments/decrements of criteria values. In this way, it also gives quantitative values of the objective function allowing stakeholders to perform a comprehensive risk analysis for a solution when it is affected by exogenous variables.

Strategic Multi-Criteria Decision Making: A Practical Guide for Complex Scenarios is divided into four parts. Part 1 is devoted to exploring the history and development of the discipline and the way it is currently used. It highlights drawbacks and problems that scholars have identified in different MCDM methods and techniques. Part 2 refers to what can be done using the MCDM process. Part 3 proposes the SIMUS method as a strategic procedure to deal with MCDM problems, and addressing how to approach complicate scenarios. Part 4 is entirely devoted to support practitioners through more than 100 questions a user may ask, and their corresponding answers, as well as a collection of solved six complex real-life scenarios. The decision-making process can be a complex task, especially with multi-criteria problems. With large amounts of information, it can be an extremely difficult to make a rational decision, due to the number of intervening variables, their interrelationships, potential solutions that might exist, diverse objectives envisioned for a project, etc. The SIMUS method has been designed to offer a strategy to help organize, classify, and evaluate this information effectively.

✦ Table of Contents

Preface and Road Map
Book Structure
Introduction
Prologue to this Second Edition
Contents
Part I: Theory and Analysis of MCDM Problems: History of MCDM and How It Is Performed
Chapter 1: Multi-criteria Decision-Making, Evolution, and Characteristics
1.1 History and Evolution of Multi-criteria Decision-Making Methods
1.1.1 Some Background Information on Decision-Making
1.2 Introduction to Most Common and Used Heuristic Methods
1.3 The Decision-Making Paradox
1.4 Which Is the Best MCDM Method?
1.5 Considering and Modelling Reality
1.6 Is It Possible to Represent Reality Faithfully?
1.7 Conclusion of This Chapter
References
Chapter 2: The Initial Decision Matrix and Its Relation with Modelling a Scenario
2.1 Basic Components of the Initial MCDM Decision Matrix
2.1.1 Stakeholders
2.1.2 Decision-Maker or Group of DMs
2.1.3 Objective/s That the Scenario Must Attain
2.1.4 Scenario/s
2.1.5 Alternatives, Projects or Options
2.1.6 Criteria
2.1.6.1 Areas Included in Criteria
2.1.6.2 Capacity of Criteria to Evaluate Alternatives
2.1.6.3 Actions for Criteria
2.1.6.4 Resources and Restrictions for Criteria
2.1.7 Performance Values
2.1.8 Decision Matrix
2.1.9 Methods
2.2 Routines to Perform with Data
2.2.1 Normalization
2.3 Rank Reversal
2.3.1 Possible Causes for RR
2.3.2 Brief Information on Rank Reversal in Different MCDM Methods
2.3.2.1 Rank Reversal in AHP
2.3.2.2 Rank Reversal in TOPSIS
2.3.2.3 Rank Reversal in PROMETHEE
2.3.2.4 Rank Reversal in ELECTRE
2.3.2.5 Rank Reversal in SAW
2.4 The Uncertain Best Solution
2.5 Characteristics of Components of the Initial Decision Matrix
2.5.1 The MCDM Process as a System
2.5.2 Alternatives Relationships
2.5.3 Alternatives Heavily Related: A Case-Selecting Proposals
2.5.4 Including and Excluding Alternatives-Conditions by a Third Party
2.5.4.1 Actual Cases
2.5.5 Forced Alternatives-An Actual Case: Fulfillment of Previous Commitments
2.5.6 Criteria Selection
2.5.7 Resources-An Actual Case: Oil Refinery
2.5.8 Criteria Range
2.5.9 Annual Budget Restriction-An Actual Case: Five Yrs Development Plan
2.5.10 Criteria Correlation
2.5.11 Risk: A Fundamental Criterion
2.5.12 Examining Differences in Results for the Same Problem Between Assumed Weights and Weights from Entropy: Case Study-Elec...
2.5.13 Working with a Variety of Performance Values-An Actual Case: Environmental Indicators
2.5.14 The Z´´ Method for Determining Some Performance Values for Qualitative Criteria 2.5.15 The Z Matrix-CASE STUDY: Determining Risk Performance Values for Inputting in Risk Criteria 2.5.16 Need to Work with Performance Values Derived from another Data Table 2.5.17 Conditioning the Decision Matrix to Obtain a Specified Number of Results 2.6 Additional Conditions Required for Methods 2.7 Sensitivity Analysis 2.7.1 The Two Types of Sensibility Analysis 2.7.2 A Critical Analysis of the Way Sensitivity Analysis Is Performed Nowadays 2.8 Conclusion of This Chapter References Part II: Theory and Analysis of MCDM Problems: What Can Be Done by Using the MCDM Process? Chapter 3: How to Shape Multiple Scenarios 3.1 Introduction 3.2 Developing the Best Strategy: Case Study-Selecting Projects for Agribusiness Activities in Different Scenarios 3.3 Solving the Problem 3.4 Conclusion of This Chapter References Chapter 4: The Decision-Maker, a Vital Component of the Decision-Making Process 4.1 Decision-Maker (DM) Functions-Interpretation of Reality 4.1.1 First Level: Building the Initial Decision Matrix 4.1.2 Second Level: Selecting a Method to Use 4.1.3 Third Level: Following the Process 4.1.4 Fourth Level: Examining the Result 4.1.5 Synergy Between the DM and the Method 4.2 Conclusion of This Chapter References Chapter 5: Design of a Decision-Making Method Reality-Wise: How Should it Be Done? 5.1 Modelling 5.2 Interpreting Reality 5.2.1 Areas Where Reality Is Not in General Interpreted 5.2.1.1 Scenarios 5.2.1.2 Alternatives 5.2.1.3 Criteria 5.2.1.4 Performance Values 5.2.1.5 Results Delivered by MCDM Methods 5.3 Check List for Aspects to Be Normally Considered When Modelling 5.4 Working Template for Modeling a Scenario in MCDM and for Selecting a Method to Solve it 5.5 Conclusion of This Chapter References Part III: Theory and Analysis of MCDM Problems: Proposes SIMUS as a Strategic Procedure to Tackle Real-World Scenarios Chapter 6: Linear Programming Fundamentals 6.1 Basic Mathematical Background 6.2 The Initial Decision Matrix (IDM) 6.3 Solving the LP Problem Graphically: Case Study-Power Plant Based on Solar Radiation 6.4 The Two Sides of a Coin 6.5 Description of the Method 6.6 Graphical Explanation of Correlation 6.7 Is Rank Reversal Present in Linear Programming? 6.8 Conclusion of This Chapter References Chapter 7: The SIMUS Method 7.1 Background Information 7.2 How SIMUS Works-Case Study: Power Plant Based on Solar Radiation 7.2.1 Normalization by SIMUS 7.3 SIMUS Application Example: Case Study-Power Plant Based on Solar Radiation 7.4 Special Circumstances 7.4.1 Ties in Scores 7.4.2 Need to Use Formulae for Performance Factors 7.4.3 Errors in the Decision Matrix 7.4.4 Dealing with Non-linear Criteria 7.5 Is SIMUS Affected by Rank Reversal? 7.6 Testing SIMUS in Rank Reversal 7.6.1 Case 1: Investment in Renewable Sources of Energy 7.6.2 Case 2: Rehabilitation of Abandoned Urban Land 7.6.3 Case 3: Determining Sustainable Indicators 7.7 Solving Multi Scenarios Simultaneously 7.7.1 Analysis of Global Solution-What to Produce and where? 7.7.2 What Projects Go into Each Scenario 7.8 Conclusion of this Chapter References Chapter 8: Sensitivity Analysis by SIMUS: The IOSA Procedure 8.1 Background Information 8.1.1 Example - Agroindustry for Export 8.2 Data that the DM Must Input in IOSA 8.3 DM Analysis 8.4 Sequence for Sensitivity Analysis by SIMUS/IOSA 8.5 Report to Stakeholders: Type of Concerns and Questions Expressed by the Stakeholders Relative to this Production Problem a... 8.6 Conclusion of this Chapter References Chapter 9: Group Decision-Making Case Study: Highway Construction 9.1 Background Information 9.2 Construction of the Decision Matrix: A Case - Construction of a Highway in China 9.3 Loading Data into SIMUS 9.4 Step-by-Step Analysis 9.5 Detailed Analysis by the Group 9.5.1 First Objective (Minimize Construction Cost) 9.5.2 Second Objective (Minimize Maintenance Cost) 9.5.3 Third Objective (Minimize Delays in Transit) 9.5.4 Four Objective (Maximize Safety) 9.5.5 Fifth Objective (Maximize Lighting) 9.5.6 Six Objectives (Minimizes Breaking Connectivity Between Areas Due to the Highway) 9.5.7 Seventh Objective (Minimize Construction Time) 9.5.8 Eighth Objective (Environmental Impacts) 9.5.9 Ninth Objective (Minimize Traffic Noise) 9.6 Conclusion of this Chapter References Chapter 10: SIMUS Applied to Quantify SWOT Strategies 10.1 Background 10.2 Procedure 10.3 Application Example: Case Study-Strategy for Fabricating Electric Cars 10.4 Construction of the Numerical SWOT Matrix 10.4.1 Market and Government 10.5 Preparing an Excel Matrix with Data 10.6 Discussion 10.7 Conclusion of This Chapter References Chapter 11: Analysis of Lack of Agreement Between MCDM Methods Related to the Solution of a Problem: Proposing a Methodology f... 11.1 Objective of this Section 11.2 Causes for Discrepancies on Results 11.3 Subjective Preferences 11.3.1 Subjective Weights 11.3.2 Objective Weights 11.3.3 Inconsistencies 11.3.4 Evaluating Results 11.3.5 The Proxy Approach 11.3.6 Selecting a MCDM Method 11.3.7 The DM Role 11.3.8 What MCDM Method Can Be Chosen as a Proxy? 11.3.9 Measuring Similitude Between Rankings 11.3.10 Example as How Rankings Can Be Compared 11.4 Conclusion of this Chapter References Part IV: Practice of Problem Solving Using MCDM: Support for Practitioners Chapter 12: Support and Guidance to Practitioners by Simulation of Questions Formulated by Readers and Detailed Answers and Ex... 12.1 Scenarios 12.2 Sequence of the MCDM Process 12.3 Criteria 12.4 Resources and Limits for Criteria 12.5 Performance Factors 12.6 Normalization 12.7 Group Decision Making 12.8 Results 12.9 SWOT 12.10 Sensitivity Analysis (SA) 12.11 Role of the Decision-Maker (DM) Chapter 13: Best Practices: Modelling and Sensitivity Analysis in MCDM 13.1 The SIMUS Method 13.2 Definitions 13.2.1 Composite Indexes 13.2.2 Macro Planning 13.2.3 Strategies 13.2.4 Alternatives 13.2.5 Criteria 13.2.6 Performance Values 13.2.7 Attributes 13.2.8 Results 13.2.9 Weights 13.2.10 Sensitivity Analysis 13.3 Modelling and the Role of Stakeholders 13.4 Areas Where SIMUS Has Been Used 13.5 Comments and Advices in Black, Examples in Italics 13.6 Recommendations to Practitioners 13.7 Complex and Complicated Scenarios 13.7.1 Background Information 13.7.2 Aspects to Consider by the DM 13.7.2.1 Data Acquisition 13.7.2.2 Criteria Selection 13.7.2.3 Weights 13.7.2.4 Criteria Units 13.7.2.5 Criteria Types 13.7.2.6 Cardinal Data 13.7.2.7 Selecting a Method 13.7.2.8 Working with a Method 13.7.2.9 Difficulties than May Be Encountered in Interpreting a Solution 13.7.2.10 Role of Sensitivity Analysis 13.8 Using SIMUS for Decision-Making 13.9 Analyzing Variations in Criteria Limits (RHS) 13.10 Analyzing Variations in Alternatives Scores 13.11 Conclusion References Chapter 14: Some Complex and Uncommon Cases Solved by SIMUS 14.1 Case Study: Simultaneous Multiple Contractors´ Selection for a Large Construction Project 14.1.1 Background Information 14.1.2 The Case: Construction of a Large Power Plant 14.1.3 Conclusion of this Case 14.2 Case Study: Quantitative Evaluation of Government Policies Regarding Penetration of Advanced Technologies 14.2.1 Background Information 14.2.2 Process Structure 14.2.3 The Case 14.2.4 Analysis of Different Policies 14.2.5 Conclusion of This Case 14.3 Case Study: Selecting Hydroelectric Projects in Central Asia 14.3.1 Background Information 14.3.2 Conclusion of This Case 14.4 Case Study: Community Infrastructure Upgrading for Villages in Ghana 14.4.1 Background Information 14.4.2 Areas and Data 14.4.2.1 Analysis 14.4.3 Conclusion for This Case 14.5 Case Study: Urban Development Study for the Extended Urban Zone of Guadalajara, According to Sustainability Indicators, M... 14.5.1 Background Information 14.5.1.1 Projects 14.5.1.2 Criteria 14.5.1.3 Project by Municipalities Considering 14.5.1.4 Projects that Are Shared for more than One Municipality 14.5.1.5 Maximum Amounts Available for Municipality Considering 14.5.1.6 Result 14.5.2 Conclusion of This Case 14.6 Case Study: Selection of the Best Route Between an Airport and the City Downtown 14.6.1 Background Information 14.6.2 The Case 14.6.3 Conclusion of This Case References Appendix The Simplex Algorithm: Its Analysis-Progressive Partial Solutions Demonstration of Absence of Rank Reversal in SIMUS Solving a Problem with SIMUS Software Adding an Exact Copy of an Existing Project Adding Project 6Worse´´ than Others
Adding New Project x7 Keeping Project x6 and with x3 = x6 = x7
Adding a New Project Identical to Other and Simultaneously Adding Another Considered the Best
Deleting Project from the Original
Summary of Scenarios and Results
Conclusion
Reference