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Description:
This third edition of the classic textbook in Optimization has been fully revised and updated. It comprehensively covers modern theoretical insights in this crucial computing area, and will be required reading for analysts and operations researchers in a variety of fields. The book connects the purely analytical character of an optimization problem, and the behavior of algorithms used to solve it. Now, the third edition has been completely updated with recent Optimization Methods. The book also has a new co-author, Yinyu Ye of California’s Stanford University, who has written lots of extra material including some on Interior Point Methods.
About The Author:
David G. Luenberger (born in 1937) is a mathematical scientist known for his research and his textbooks, which center on mathematical optimization. He is a professor in the department of Management Science and Engineering at Stanford University.
Main Contents:
Chapter 1. Introduction 1.
PART I Linear Programming.
Chapter 2. Basic Properties of Linear Programs 11.
Chapter 3. The Simplex Method 33.
Chapter 4. Duality 79.
Chapter 5. Interior-Point Methods 111.
Chapter 6. Transportation and Network Flow Problems 145.
PART II Unconstrained Problems.
Chapter 7. Basic Properties of Solutions and Algorithms 183.
Chapter 8. Basic Descent Methods 215.
Chapter 9. Conjugate Direction Methods 263.
Chapter 10. Quasi-Newton Methods 285.
PART III Constrained Minimization.
Chapter 11. Constrained Minimization Conditions 321.
Chapter 12. Primal Methods 359.
Chapter 13. Penalty and Barrier Methods 401.
Chapter 14. Dual and Cutting Plane Methods 435.
Chapter 15. Primal-Dual Methods 469.
Appendix A. Mathematical Review 507.
Appendix B. Convex Sets 515.
Appendix C. Gaussian Elimination 523.
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