The book is heavily and badly highlighted. There are pages with an X in a heavy marker that render these pages useless. I am pretty unhappy with the book it is extremely difficult to read because of these marks and the price I payed was quite high. I would have returned it if it was not for the hazard of dealing with shipping back and fore.
Author(s): Igor Griva, Stephen G. Nash, Ariela Sofer
Edition: 2
Publisher: Society for Industrial Mathematics
Year: 2008
Language: English
Pages: 766
Contents......Page 7
Preface......Page 15
Part I - Basics......Page 25
Ch 1. Optimization Models......Page 27
Ch 2. Fundamentals of Optimization......Page 67
Ch 3. Representation of Linear Constraints......Page 101
Part II - Linear Programming......Page 119
Ch 4. Geometry of Linear Programming......Page 121
Ch 5. The Simplex Method......Page 149
Ch 6. Duality and Sensitivity......Page 197
Ch 7. Enhancements of the Simplex Method......Page 237
Ch 8. Network Problems......Page 295
Ch 9. Computational Complexity of Linear Programming......Page 325
Ch 10. Interior-Point Methods for Linear Programming......Page 343
Part III - Unconstrained Optimization......Page 379
Ch 11. Basics of Unconstrained Optimization......Page 381
Ch 12. Methods for Unconstrained Optimization......Page 425
Ch 13. Low-Storage Methods for Unconstrained Problems......Page 475
Part IV - Nonlinear Optimization......Page 505
Ch 14. Optimality Conditions for Constrained Problems......Page 507
Ch 15. Feasible-Point Methods......Page 573
Ch 16. Penalty and Barrier Methods......Page 625
Part V - Appendices......Page 683
Appendix A: Topics from Linear Algebra......Page 685
Appendix B: Other Fundamentals......Page 715
Appendix C: Software......Page 727
Bibliography......Page 731
Index......Page 751
