Preface
Part I: Basics
Chapter 1: Optimization Models
Chapter 2: Fundamentals of Optimization
Chapter 3: Representation of Linear Constraints
Part II: Linear Programming
Chapter 4: Geometry of Linear Programming
Chapter 5: The Simplex Method
Chapter 6: Duality and Sensitivity
Chapter 7: Enhancements of the Simplex Method
Chapter 8: Network Problems
Chapter 9: Computational Complexity of Linear Programming
Chapter 10: Interior-Point Methods of Linear Programming
Part III: Unconstrained Optimization
Chapter 11: Basics of Unconstrained Optimization
Chapter 12: Methods for Unconstrained Optimization
Chapter 13: Low-Storage Methods for Unconstrained Problems
Part IV: Nonlinear Optimization
Chapter 14: Optimality Conditions for Constrained Problems
Chapter 15: Feasible-Point Methods
Chapter 16: Penalty and Barrier Methods
Part V: Appendices
Appendix A: Topics from Linear Algebra
Appendix B: Other Fundamentals
Appendix C: Software
Bibliography
Index
