Mathematical modelling of decision problems : using the SIMUS method for complex scenarios / / Nolberto Munier

• Autore: Munier Nolberto
• Pubblicazione: Cham, Switzerland : , : Springer, , [2021]; ©2021
• Descrizione fisica: 1 online resource (212 pages)
• Disciplina: 658.403
• Soggetto topico: Multiple criteria decision making - Mathematical models
• Nota di contenuto: Intro -- Preface -- Reference -- Contents -- Chapter 1: MCDM Methods: Modelling, Feasibility, and Sensitivity Analysis -- 1.1 Introduction -- 1.1.1 Present-Day Condition of MCDM -- 1.1.2 Are MCDM Methods Reliable or They Are Only a Useful Guide? -- 1.1.3 Modelling -- 1.1.4 Project Feasibility -- 1.1.4.1 A Fundamental Question: Is a Problem Feasible? -- 1.1.5 As Done at Present, Sensitivity Analysis Is Not Reliable -- 1.2 Conclusion -- References -- Chapter 2: Linear Programming and the SIMUS Method -- 2.1 Linear Programming -- 2.2 The SIMUS Method -- 2.2.1 SIMUS and Sensitivity Analysis -- 2.2.2 How SIMUS Considers the Significance of Criteria? -- 2.2.3 The Role of the DM -- 2.3 Conclusion -- References -- Chapter 3: Analysis of Facts: Issues and Questions Answered in MCDM Practice -- 3.1 Which Are Complex Scenarios? -- 3.2 Why There Could Be Precedence Between Projects, What Do They Mean? -- 3.3 Why Most Methods Do Not Consider Resources? -- 3.4 Why There Is a Necessity to Consider All Aspects of a Project and Not Only the Most Important? -- 3.5 How Are Resources Considered? -- 3.6 Which Are Determined First, Alternatives or Criteria, and Why? -- 3.7 How to Work with Multiple Scenarios? -- 3.8 Can a Criterion Impact on Another? -- 3.9 Are Alternatives Related or They Are Always Independent? -- 3.10 What Is a Binary Criterion, and What Is Its Purpose? -- 3.11 What Happens When Projects in a Portfolio Need to Be Started at Different Times? -- 3.12 How Do We Work with Group Decision-Making? -- 3.13 What Relationships May Exist Among Resources? -- 3.14 Is it Possible to Work with Negative Performance Values? -- 3.15 What Is Rank Reversal (RR)? -- 3.16 How Do we Know How Well Each Criterion Is Satisfied? -- 3.17 What Is the Strength of a Solution? -- 3.18 How Criteria Are Chosen for Sensitivity Analysis?. ; 3.19 How to Proceed When the Result Shows Ties Between Alternatives Scores? -- 3.20 What Happens When There Is a Shortage of Resources? -- 3.21 How to Choose Alternatives When Subject to Conditional Criteria? -- 3.22 How to Compute Objective Weights? -- 3.23 How to Proceed When Alternatives Are Already Specified, but Must Be Performed at Different Time Periods? -- 3.24 How Do We Work with Geographic Information System (GIS)? -- 3.25 Considering Technical Aspects -- 3.26 What Are Multiples Scenarios? -- 3.27 Forecasting Risks -- 3.28 When to Use Fuzzy Logic? -- 3.29 What Are the Aichi Biodiversity Targets and How Can They Be Used as Criteria? -- 3.30 What Is the Meaning of Structures in MCDM Methods? -- 3.31 Why in Some Problems Not All Alternatives Get Ranked? -- 3.32 Is it Possible That a Certain Criterion Calls for Maximization and Also for Minimization? -- 3.33 What Is a Composite Index and How Can We Build It? -- 3.34 What Is Planning at Macro Level? -- 3.35 Is It Possible to Validate a Result or a MCDM Method? -- 3.36 How to Work with Negative Objectives? -- 3.37 Why Do We Need to Work with Objective Weights Instead of Subjective Weights? -- 3.38 How to Proceed When in Two Portfolios with Different Projects, the Second Portfolio Depends on the First? -- 3.39 How to Proceed with Portfolios of Projects in Series? -- 3.40 Can Resources Be Interrelated? -- 3.41 Is It Convenient to Partition a Project, Solve Each Part and Then Solving? -- 3.42 How to Work with Projects That Must Be Forcefully Shared Between Several Sites? -- 3.43 How to Work When in the Initial Decision Matrix, the Performance Values Are Probabilities? -- 3.44 How to Work with Weights? -- 3.45 Conclusion -- References -- Chapter 4: Analysis of Questions Normally Formulated on MCDM -- 4.1 Is the Top-Down Approach, Correct? -- 4.2 Is It Reasonable to Use Pair-Wise Comparisons in MCDM?. ; 4.3 The Entropy Concept -- 4.4 Why Different Methods Give a Different Ranking for the Same Problem? -- 4.5 Which Is the Best MCDM Method? -- 4.6 Why Decision-Making Using Preferences Should Be Avoided? -- 4.7 Which Is the Best Normalization Procedure? -- 4.8 Is It Convenient to Use a Linear Hierarchy in MCDM? -- 4.9 Is It Possible to Affirm That a MCDM Solution Can Be Validated? -- 4.10 What Information Can Be Extracted from MCDM Methods? -- 4.11 Ties in Alternatives -- 4.12 Conditions to Be Met to Perform an Efficient Sensitivity Analysis -- 4.13 Strategic Analysis -- 4.14 How to Select the MCDM Method That Best Fits a Problem? -- 4.15 Hidden Factors -- 4.16 How to Reduce the Number of Alternatives? -- 4.17 Is It Always the Best Alternative Selected the One to Be Adopted? -- 4.18 Is Fuzzy Logic Useful in the MCDM Context? -- 4.19 What Are the Criteria? -- 4.20 How to Proceed When Alternatives Are Also Subject to Compliance with a Certain Number of Criteria? -- 4.21 What If We Need the Results Expressed in Quantities? -- 4.22 Planning Resources: How to Compute the Quantity of Resources Required for a Scenario? -- 4.23 What Is a Compromise Solution? -- 4.24 What Is Compensation? -- 4.25 Can We Disaggregate or Partition a Project? -- 4.26 How to Perform Sensitivity Analysis Considering Performance Values? -- 4.27 A Case: Not Sufficient Research Rendered an Unacceptable Solution -- 4.28 Conclusion -- References -- Further Reading -- Chapter 5: Putting SIMUS to Work -- 5.1 What Platform Does SIMUS Use? -- 5.2 What Can the User Do with SIMUS? -- 5.3 Examples of Applications in Different Areas -- 5.4 Background Information -- 5.5 How SIMUS Works? -- 5.5.1 Sensitivity Analysis -- 5.6 Step-by-Step Procedure Using SIMUS -- 5.7 Operation -- 5.7.1 Additional Characteristics -- 5.8 Particular Scenarios -- 5.8.1 When There Is Dependency Between Projects. ; 5.8.2 When There Are Project Alliances (Joint Ventures) -- 5.8.3 When the Result Must Be Expressed in Binary -- 5.8.4 When There Is a Need to Have Results in Integers -- 5.8.5 When Alternatives Are Inclusive or Exclusive According to Criteria -- 5.8.6 When There Is Need to Rank Projects in a Portfolio -- 5.8.7 When There Is Shortage of Funds to Execute All Projects in the Portfolio -- 5.8.8 When Selection for Projects Is Linked with Planning and Scheduling Along Several Years -- 5.8.9 When Projects Are Related to Funds Availability -- 5.8.10 When Selection Must Consider That Projects May Have Different Percentages of Completion -- 5.9 Sensitivity Analysis -- 5.9.1 Checking Robustness -- 5.10 Conclusion -- References -- Appendix -- Chapter 12 (No Author Mentioned) -- Alternatives -- Compensatory Methods -- Correlation -- Criteria -- Different Results -- Entropy -- Forecasting -- Inconsistency -- Independence of Criteria -- Modelling -- Normalization -- Objectives -- Partitioning -- Preferences -- Pair-Wise Comparisons -- Publishing -- Rankings -- Rank Reversal -- Results -- Scales -- Stakeholders -- Weights -- References.
• Titolo autorizzato: Mathematical Modelling of Decision Problems
• ISBN: 3-030-82347-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910506377403321
• Lo trovi qui: Univ. Federico II
• Serie: Multiple Criteria Decision Making