Joao Luis De Miranda
Introduction to Optimization-Based Decision-Making
Joao Luis De Miranda
Introduction to Optimization-Based Decision-Making
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This book provides an elementary and self-contained introduction to the basic concepts involved in making decisions in an optimization-based environment. The mathematical level of the text is directed to the post-secondary reader, or university students in the initial years.
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This book provides an elementary and self-contained introduction to the basic concepts involved in making decisions in an optimization-based environment. The mathematical level of the text is directed to the post-secondary reader, or university students in the initial years.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Chapman and Hall/CRC
- Seitenzahl: 266
- Erscheinungstermin: 27. Mai 2024
- Englisch
- Abmessung: 229mm x 152mm x 14mm
- Gewicht: 390g
- ISBN-13: 9781032119779
- ISBN-10: 1032119772
- Artikelnr.: 70354232
- Verlag: Chapman and Hall/CRC
- Seitenzahl: 266
- Erscheinungstermin: 27. Mai 2024
- Englisch
- Abmessung: 229mm x 152mm x 14mm
- Gewicht: 390g
- ISBN-13: 9781032119779
- ISBN-10: 1032119772
- Artikelnr.: 70354232
João Luís de Miranda is Professor at ESTG-Escola Superior de Tecnologia e Gestão (IPPortalegre) and Researcher in Optimization methods and Process Systems Engineering (PSE) at CERENA-Centro de Recursos Naturais e Ambiente (IST/ULisboa). He has been teaching for more than twenty years in the field of Mathematics (e.g., Calculus, Operations Research-OR, Management Science-MS, Numerical Methods, Quantitative Methods, Statistics) and has authored/edited several publications in Optimization, PSE, and Education subjects in Engineering and OR/MS contexts. João Luís de Miranda is addressing the research subjects through international cooperation in multidisciplinary frameworks, and is serving on several boards/committees at national and European level.
1. First Notes on Optimization for Decision Support. 1.1. Introduction.
1.2. First Steps. 1.3. Introducing Proportionality. 1.4. A Non-Proportional
Instance. 1.5. An Enlarged and Non-Proportional Instance. 1.6. Concluding
Remarks. 2. Linear Algebra. 2.1. Introduction. 2.2. Gauss Elimination on
the Linear System. 2.3. Gauss Elimination with the Augmented Matrix. 2.4.
Gauss-Jordan and the Inverse Matrix. 2.5. Cramer's Rule and Determinants.
2.6. Concluding Remarks. 3. Linear Programming Basics. 3.1. Introduction.
3.2. Graphical Approach. 3.3. Algebraic Form. 3.4. Tableau Form. 3.5.
Matrix Form. 3.6. Updating the Inverse Matrix. 3.7. Concluding Remarks. 4.
Duality. 4.1. Introduction. 4.2. Primal-Dual Transformations. 4.3. Dual
Simplex Method. 4.4. Duality Properties. 4.5. Duality and Economic
Interpretation. 4.6. A First Approach to Optimality Analysis. 4.7.
Concluding Remarks. 5. Calculus Optimization. 5.1. Introduction. 5.2.
Constrained Optimization with Lagrange Multipliers. 5.3. Generalization of
the Constrained Optimization Case. 5.4. Lagrange Multipliers for the
Furniture Factory Problem. 5.5. Concluding Remarks. 6. Optimality Analysis.
6.1. Introduction. 6.2. Revising LP Simplex. 6.3. Sensitivity Analysis.
6.4. Parametric Analysis. 6.5. Concluding Remarks. 7. Integer Linear
Programming. 7.1. Introduction. 7.2. Solving Integer Linear Programming
Problems. 7.3. Modeling with Binary Variables. 7.4. Solving Binary Integer
Programming Problems. 7.5. Concluding Remarks. 8. Game Theory. 8.1.
Introduction. 8.2. Constant-Sum Game. 8.3. Zero-Sum Game. 8.4. Mixed
Strategies - LP Approach. 8.5. Dominant Strategies. 8.6. Concluding
Remarks. 9. Decision Making Under Uncertainty. 9.1. Introduction. 9.2.
Multiple Criteria and Decision Maker Values. 9.3. Capacity Expansion for
the Furniture Factory. 9.4. A Comparison Analysis. 9.5. Concluding Remarks.
10. Robust Optimization. 10.1. Introduction. 10.2. Notes on Stochastic
Programming. 10.3. Robustness Promotion on Models and Solutions. 10.4.
Models Generalization onto Robust Optimization. 10.5. Concluding Remarks.
Selected References
1.2. First Steps. 1.3. Introducing Proportionality. 1.4. A Non-Proportional
Instance. 1.5. An Enlarged and Non-Proportional Instance. 1.6. Concluding
Remarks. 2. Linear Algebra. 2.1. Introduction. 2.2. Gauss Elimination on
the Linear System. 2.3. Gauss Elimination with the Augmented Matrix. 2.4.
Gauss-Jordan and the Inverse Matrix. 2.5. Cramer's Rule and Determinants.
2.6. Concluding Remarks. 3. Linear Programming Basics. 3.1. Introduction.
3.2. Graphical Approach. 3.3. Algebraic Form. 3.4. Tableau Form. 3.5.
Matrix Form. 3.6. Updating the Inverse Matrix. 3.7. Concluding Remarks. 4.
Duality. 4.1. Introduction. 4.2. Primal-Dual Transformations. 4.3. Dual
Simplex Method. 4.4. Duality Properties. 4.5. Duality and Economic
Interpretation. 4.6. A First Approach to Optimality Analysis. 4.7.
Concluding Remarks. 5. Calculus Optimization. 5.1. Introduction. 5.2.
Constrained Optimization with Lagrange Multipliers. 5.3. Generalization of
the Constrained Optimization Case. 5.4. Lagrange Multipliers for the
Furniture Factory Problem. 5.5. Concluding Remarks. 6. Optimality Analysis.
6.1. Introduction. 6.2. Revising LP Simplex. 6.3. Sensitivity Analysis.
6.4. Parametric Analysis. 6.5. Concluding Remarks. 7. Integer Linear
Programming. 7.1. Introduction. 7.2. Solving Integer Linear Programming
Problems. 7.3. Modeling with Binary Variables. 7.4. Solving Binary Integer
Programming Problems. 7.5. Concluding Remarks. 8. Game Theory. 8.1.
Introduction. 8.2. Constant-Sum Game. 8.3. Zero-Sum Game. 8.4. Mixed
Strategies - LP Approach. 8.5. Dominant Strategies. 8.6. Concluding
Remarks. 9. Decision Making Under Uncertainty. 9.1. Introduction. 9.2.
Multiple Criteria and Decision Maker Values. 9.3. Capacity Expansion for
the Furniture Factory. 9.4. A Comparison Analysis. 9.5. Concluding Remarks.
10. Robust Optimization. 10.1. Introduction. 10.2. Notes on Stochastic
Programming. 10.3. Robustness Promotion on Models and Solutions. 10.4.
Models Generalization onto Robust Optimization. 10.5. Concluding Remarks.
Selected References
1. First Notes on Optimization for Decision Support. 1.1. Introduction.
1.2. First Steps. 1.3. Introducing Proportionality. 1.4. A Non-Proportional
Instance. 1.5. An Enlarged and Non-Proportional Instance. 1.6. Concluding
Remarks. 2. Linear Algebra. 2.1. Introduction. 2.2. Gauss Elimination on
the Linear System. 2.3. Gauss Elimination with the Augmented Matrix. 2.4.
Gauss-Jordan and the Inverse Matrix. 2.5. Cramer's Rule and Determinants.
2.6. Concluding Remarks. 3. Linear Programming Basics. 3.1. Introduction.
3.2. Graphical Approach. 3.3. Algebraic Form. 3.4. Tableau Form. 3.5.
Matrix Form. 3.6. Updating the Inverse Matrix. 3.7. Concluding Remarks. 4.
Duality. 4.1. Introduction. 4.2. Primal-Dual Transformations. 4.3. Dual
Simplex Method. 4.4. Duality Properties. 4.5. Duality and Economic
Interpretation. 4.6. A First Approach to Optimality Analysis. 4.7.
Concluding Remarks. 5. Calculus Optimization. 5.1. Introduction. 5.2.
Constrained Optimization with Lagrange Multipliers. 5.3. Generalization of
the Constrained Optimization Case. 5.4. Lagrange Multipliers for the
Furniture Factory Problem. 5.5. Concluding Remarks. 6. Optimality Analysis.
6.1. Introduction. 6.2. Revising LP Simplex. 6.3. Sensitivity Analysis.
6.4. Parametric Analysis. 6.5. Concluding Remarks. 7. Integer Linear
Programming. 7.1. Introduction. 7.2. Solving Integer Linear Programming
Problems. 7.3. Modeling with Binary Variables. 7.4. Solving Binary Integer
Programming Problems. 7.5. Concluding Remarks. 8. Game Theory. 8.1.
Introduction. 8.2. Constant-Sum Game. 8.3. Zero-Sum Game. 8.4. Mixed
Strategies - LP Approach. 8.5. Dominant Strategies. 8.6. Concluding
Remarks. 9. Decision Making Under Uncertainty. 9.1. Introduction. 9.2.
Multiple Criteria and Decision Maker Values. 9.3. Capacity Expansion for
the Furniture Factory. 9.4. A Comparison Analysis. 9.5. Concluding Remarks.
10. Robust Optimization. 10.1. Introduction. 10.2. Notes on Stochastic
Programming. 10.3. Robustness Promotion on Models and Solutions. 10.4.
Models Generalization onto Robust Optimization. 10.5. Concluding Remarks.
Selected References
1.2. First Steps. 1.3. Introducing Proportionality. 1.4. A Non-Proportional
Instance. 1.5. An Enlarged and Non-Proportional Instance. 1.6. Concluding
Remarks. 2. Linear Algebra. 2.1. Introduction. 2.2. Gauss Elimination on
the Linear System. 2.3. Gauss Elimination with the Augmented Matrix. 2.4.
Gauss-Jordan and the Inverse Matrix. 2.5. Cramer's Rule and Determinants.
2.6. Concluding Remarks. 3. Linear Programming Basics. 3.1. Introduction.
3.2. Graphical Approach. 3.3. Algebraic Form. 3.4. Tableau Form. 3.5.
Matrix Form. 3.6. Updating the Inverse Matrix. 3.7. Concluding Remarks. 4.
Duality. 4.1. Introduction. 4.2. Primal-Dual Transformations. 4.3. Dual
Simplex Method. 4.4. Duality Properties. 4.5. Duality and Economic
Interpretation. 4.6. A First Approach to Optimality Analysis. 4.7.
Concluding Remarks. 5. Calculus Optimization. 5.1. Introduction. 5.2.
Constrained Optimization with Lagrange Multipliers. 5.3. Generalization of
the Constrained Optimization Case. 5.4. Lagrange Multipliers for the
Furniture Factory Problem. 5.5. Concluding Remarks. 6. Optimality Analysis.
6.1. Introduction. 6.2. Revising LP Simplex. 6.3. Sensitivity Analysis.
6.4. Parametric Analysis. 6.5. Concluding Remarks. 7. Integer Linear
Programming. 7.1. Introduction. 7.2. Solving Integer Linear Programming
Problems. 7.3. Modeling with Binary Variables. 7.4. Solving Binary Integer
Programming Problems. 7.5. Concluding Remarks. 8. Game Theory. 8.1.
Introduction. 8.2. Constant-Sum Game. 8.3. Zero-Sum Game. 8.4. Mixed
Strategies - LP Approach. 8.5. Dominant Strategies. 8.6. Concluding
Remarks. 9. Decision Making Under Uncertainty. 9.1. Introduction. 9.2.
Multiple Criteria and Decision Maker Values. 9.3. Capacity Expansion for
the Furniture Factory. 9.4. A Comparison Analysis. 9.5. Concluding Remarks.
10. Robust Optimization. 10.1. Introduction. 10.2. Notes on Stochastic
Programming. 10.3. Robustness Promotion on Models and Solutions. 10.4.
Models Generalization onto Robust Optimization. 10.5. Concluding Remarks.
Selected References