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1.

Book
Book
1. Introduction to optimization techniques : fundamentals and applications of nonlinear programming
Masanao Aoki
Published: New York : Macmillan, c1971  xvi, 335 p. ; 24 cm
Series: Macmillan series in applied computer sciences
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2.

Book
Book
2. Nonlinear programming : analysis and methods
Mordecai Avriel
Published: Englewood Cliffs, N.J. : Prentice-Hall, c1976  xv, 512 p. ; 24 cm
Series: Prentice-Hall series in automatic computation
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3.

Book
Book
3. Nonlinear programming : theory and algorithms
Mokhtar S. Bazaraa, C.M. Shetty
Published: New York : Wiley, c1979  xiv, 560 p. ; 24 cm
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Table of Contents: Read more
Introduction. / Chapter 1：
Problem Statement and Basic Definitions / 1.1：
Illustrative Examples / 1.2：
Guidelines for Model Construction / 1.3：
Exercises
Notes and References
Convex Analysis. / Part 1：
Convex Sets. / Chapter 2：
Convex Hulls / 2.1：
Closure and Interior of a Set / 2.2：
Weierstrass's Theorem / 2.3：
Separation and Support of Sets / 2.4：
Convex Cones and Polarity / 2.5：
Polyhedral Sets, Extreme Points, and Extreme Directions / 2.6：
Linear Programming and the Simplex Method / 2.7：
Convex Functions and Generalizations. / Chapter 3：
Definitions and Basic Properties / 3.1：
Subgradients of Convex Functions / 3.2：
Differentiable Convex Functions / 3.3：
Minima and Maxima of Convex Functions / 3.4：
Generalizations of Convex Functions / 3.5：
Optimality Conditions and Duality. / Part 2：
The Fritz John and Karush-Kuhn-Tucker Optimality Conditions. / Chapter 4：
Unconstrained Problems / 4.1：
Problems Having Inequality Constraints / 4.2：
Problems Having Inequality and Equality Constraints / 4.3：
Second-Order Necessary and Sufficient Optimality Conditions for Constrained Problems / 4.4：
Constraint Qualifications. / Chapter 5：
Cone of Tangents / 5.1：
Other Constraint Qualifications / 5.2：
Lagrangian Duality and Saddle Point Optimality Conditions. / 5.3：
Lagrangian Dual Problem / 6.1：
Duality Theorems and Saddle Point Optimality Conditions / 6.2：
Properties of the Dual Function / 6.3：
Formulating and Solving the Dual Problem / 6.4：
Getting the Primal Solution / 6.5：
Linear and Quadratic Programs / 6.6：
Algorithms and Their Convergence / Part 3：
The Concept of an Algorithm. / Chapter 7：
Algorithms and Algorithmic Maps / 7.1：
Closed Maps and Convergence / 7.2：
Composition of Mappings / 7.3：
Comparison Among Algorithms / 7.4：
Unconstrained Optimization. / Chapter 8：
Line Search Without Using Derivatives / 8.1：
Line Search Using Derivatives / 8.2：
Some Practical Line Search Methods / 8.3：
Closedness of the Line Search Algorithmic Map / 8.4：
Multidimensional Search Without Using Derivatives / 8.5：
Multidimensional Search Using Derivatives / 8.6：
Modification of Newton's Method: Levenberg-Marquardt and Trust Region Methods / 8.7：
Methods Using Conjugate Directions: Quasi-Newton and Conjugate Gradient Methods / 8.8：
Subgradient Optimization Methods / 8.9：
Penalty and Barrier Functions. / Chapter 9：
Concept of Penalty Functions / 9.1：
Exterior Penalty Function Methods / 9.2：
Exact Absolute Value and Augmented Lagrangian Penalty Methods / 9.3：
Barrier Function Methods / 9.4：
Polynomial-Time Interior Point Algorithms for Linear Programming Based on a Barrier Function / 9.5：
Methods of Feasible Directions. / Chapter 10：
Method of Zoutendijk / 10.1：
Convergence Analysis of the Method of Zoutendijk / 10.2：
Successive Linear Programming Approach / 10.3：
Successive Quadratic Programming or Projected Lagrangian Approach / 10.4：
Gradient Projection Method of Rosen / 10.5：
Reduced Gradient Method of Wolfe and Generalized Reduced Gradient Method / 10.6：
Convex-Simplex Method of Zangwill / 10.7：
Effective First- and Second-Order Variants of the Reduced Gradient Method / 10.8：
Linear Complementary Problem, and Quadratic, Separable, Fractional, and Geometric Programming. / Chapter 11：
Linear Complementary Problem / 11.1：
Convex and Nonconvex Quadratic Programming: Global Optimization Approaches / 11.2：
Separable Programming / 11.3：
Linear Fractional Programming / 11.4：
Geometric Programming / 11.5：
Mathematical Review. / Appendix A：
Summary of Convexity, Optimality Conditions, and Duality. / Appendix B：
Bibliography.
Index
Introduction. / Chapter 1：
Problem Statement and Basic Definitions / 1.1：
Illustrative Examples / 1.2：
4.

Book
Book
4. An algorithmic approach to nonlinear analysis and optimization
[by] Edward J. Beltrami
Published: New York : Academic Press, 1970  xiv, 235 p. ; 24 cm
Series: Mathematics in science and engineering : a series of monographs and textbooks ; v. 63
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5.

Book
Book
5. The mathematics of nonlinear programming (: us ; : gw)
Anthony L. Peressini, Francis E. Sullivan, J. Jerry Uhl, Jr.
Published: New York ; Tokyo : Springer-Verlag, c1988  x, 273 p. ; 25 cm
Series: Undergraduate texts in mathematics
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Table of Contents: Read more
Preface
Unconstrained Optimization via Calculus / 1：
Convex and Convex Functions / 2：
Iterative Methods for Unconstrained Optimization / 3：
Least Squares Optimization / 4：
Convex Programming and the Karush-Kuhn-Tucker Conditions / 5：
Penalty Methods / 6：
Optimization with Equality Constraints / 7：
Index
Preface
Unconstrained Optimization via Calculus / 1：
Convex and Convex Functions / 2：
6.

Book
Book
6. Studies in linear and non-linear programming (: hard ; : pbk)
by Kenneth J. Arrow, Leonid Hurwicz, Hirofumi Uzawa ; with contributions by Hollis B. Chenery ... [et al.]
Published: Stanford, Calif. : Stanford University Press, 1958  229 p. ; 26 cm
Series: Stanford mathematical studies in the social sciences ; 2
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7.

Book
Book
7. Nonlinear programming
editor, J. Abadie ; contributors, S. Vajda ... [et al.]
Published: Amsterdam : North-Holland, 1967  xxii, 316 p. ; 23 cm
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8.

Book
Book
8. Nonlinear programming : sequential unconstrained minimization techniques
[by] Anthony V. Fiacco [and] Garth P. McCormick
Published: New York : Wiley, c1968  xiv, 210 p. ; 23 cm
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9.

Book
Book
9. Constrained global optimization : algorithms and applications (: gw ; : us)
P.M. Pardalos, J.B. Rosen
Published: Berlin ; Tokyo : Springer-Verlag, c1987  vii, 143 p. ; 25 cm
Series: Lecture notes in computer science ; 268
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10.

Book
Book
10. Nondifferentiable optimization and polynomial problems
Naum Z. Shor
Published: Boston : Kluwer, 1998  xvii, 394p ; 25cm
Series: Nonconvex optimization and its applications ; v. 24
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11.

Book
Book
11. Convex analysis and global optimization
by Hoang Tuy
Published: Dordrecht : Kluwer Academic Publishers, c1998  xi, 339 p. ; 25 cm
Series: Nonconvex optimization and its applications ; v. 22
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12.

Book
Book
12. Developments in global optimization
Immanuel M. Bomze ... [et al.]
Published: Dordrecht : Kluwer Academic Publishers, c1997  xi, 348 p. ; 25 cm
Series: Nonconvex optimization and its applications ; v. 18
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Table of Contents: Read more
Preface
NOP - A Compact Input Format for Nonlinear Optimization Problems / A. Neumaier1：
GLOPT - A Program for Constrained Global Optimization / S. Dallwig, et al.2：
Global Optimization for Imprecise Problems / M.N. Vrahatis, et al.3：
New Results on Gap-Treating Techniques in Extended Interval Newton Gauss-Seidel Steps for Global Optimization / D. Ratz4：
Quadratic Programming with Box Constraints / P.L. De Angelis5：
Evolutionary Approach to The Maximum Clique Problem: Empirical Evidence on a Larger Scale / I. Bomze, et al.6：
Interval and Bounding Hessians / C. Stephens7：
On Global Search for Non-Convex Optimal Control Problems / A. Strekalovsky ; I. Vasiliev8：
A Multistart Linkage Algorithm Using First Derivatives / C.J. Price9：
Convergence Speed of an Integral Method for Computing the Essential Supremum / J. Hichert, et al.10：
Complexity Analysis Integrating Pure Adaptive Search (PAS) and Pure Random Search (PRS) / Z.B. Zabinsky ; B.P. Kristinsdottir11：
LGO - A Program System for Continuous and Lipschitz Global Optimization / J.D. Pintèr12：
A Method Using Local Tuning For Minimizing Functions with Lipschitz Derivatives / Ya.D. Sergeyev13：
Molecular Structure Prediction by Global Optimization / K.A. Dill, et al.14：
Optimal Renewal Policy for Slowly Degrading Systems / A. Pfening ; M. Telek15：
Numerical Prediction of Crystal Structures by Simulated Annealing / W. Bollweg, et al.16：
Multidimensional Optimization in Image Reconstruction from Projections / I. Garciacute;a, et al.17：
Greedy Randomized Adaptive Search for a Location Problem with Economies of Scale / K. Holmqvist, et al.18：
An Algorithm for Improving the Bounding Procedure in Solving Process Network Synthesis by a B&B Method / B. Imreh, et al.19：
Preface
NOP - A Compact Input Format for Nonlinear Optimization Problems / A. Neumaier1：
GLOPT - A Program for Constrained Global Optimization / S. Dallwig, et al.2：
13.

Book
Book
13. Handbook of global optimization ([v. 1] ; v. 2)
edited by Reiner Horst and Panos M. Pardalos
Published: Dordrecht : Kluwer Academic, c1995-c2002  2 v. ; 25 cm
Series: Nonconvex optimization and its applications ; v. 2, v. 62
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14.

Book
Book
14. Introduction to global optimization (: hbk ; : pbk)
by Reiner Horst, Panos M. Pardalos, and Nguyen V. Thoai
Published: Dordrecht ; Boston : Kluwer Academic Publishers, c1995  xii, 318 p. ; 25 cm
Series: Nonconvex optimization and its applications ; v. 3
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15.

Book
Book
15. Nonlinear and dynamic programming
by G. Hadley
Published: Reading, Mass. : Addison-Wesley Pub., 1964  xi, 484 p. ; 24 cm
Series: Addison-Wesley series in management science and economics
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16.

Book
Book
16. Nonlinear programming
Olvi L. Mangasarian
Published: New York : McGraw-Hill, c1969  xiii, 220 p. ; 23 cm
Series: McGraw-Hill series in systems science
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Table of Contents: Read more
Preface to the Classic Edition
The Nonlinear Programming Problem, Preliminary Concepts, and Notation / Chapter 1：
Linear Inequalities and Theorems of the Alternative / Chapter 2：
Convex Sets in Rn / Chapter 3：
Convex and Concave Functions / Chapter 4：
Saddlepoint Optimality Criteria in Nonlinear Programming Without Differentiability / Chapter 5：
Differentiable Convex and Concave Functions / Chapter 6：
Optimality Criteria in Nonlinear Programming with Differentiability / Chapter 7：
Duality in Nonlinear Programming / Chapter 8：
Generalizations of Convex Functions: Quasiconvex, Strictly Quasiconvex, and Pseudoconvex Functions / Chapter 9：
Optimality and Duality for Generalized Convex and Concave Functions / Chapter 10：
Optimality and Duality in the Presence of Nonlinear Equality Constraints / Chapter 11：
Vectors and Matrices / Appendix A：
Resume of Some Topological Properties of Rn / Appendix B：
Continuous and Semicontinuous Functions, Minima and Infima / Appendix C：
Differentiable Functions, Mean-value and Implicit Function Theorems / Appendix D：
Bibliography
Name Index
Subject Index
Preface to the Classic Edition
The Nonlinear Programming Problem, Preliminary Concepts, and Notation / Chapter 1：
Linear Inequalities and Theorems of the Alternative / Chapter 2：
17.

Book
Book
17. A collection of test problems for constrained global optimization algorithms (: gw ; : us)
C.A. Floudas, P.M. Pardalos
Published: Berlin ; New York ; Tokyo : Springer-Verlag, c1990  xiv, 180 p. ; 25 cm
Series: Lecture notes in computer science ; 455
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18.

Book
Book
18. Nonlinear and dynamic programming
by G. Hadley
Published: Reading, Mass. : Addison-Wesley Pub. Co, [1970], c1964  xi, 484 p. ; 22 cm
Series: Addison-Wesley world student series
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19.

Book
Book
19. Nichtlineare programmierung
von H.P. Künzi und W. Krelle ; unter Mitwirkung von Werner Oettli
Published: Berlin ; Göttingen ; Heidelberg : Springer-Verlag, 1962  xiii, 221 p. ; 24 cm
Series: Monographien zur Unternehmensforschung = Monographs on Operations Research ; Bd. 1
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20.

Book
Book
20. Nonlinear and dynamic programming ; an introduction (: us ; : au)
Sven Danø
Published: New York ; Wien : Springer-Verlag, 1975  164 p. ; 24 cm
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21.

Book
Book
21. Computational methods in optimization : a unified approach
E. Polak
Published: New York : Academic Press, 1971  xvii, 329 p. ; 24 cm
Series: Mathematics in science and engineering : a series of monographs and textbooks ; v. 77
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22.

Book
Book
22. Introduction to material and energy balances
G.V. Reklaitis ; with contributions by Daniel R. Schneider
Published: New York : Wiley, c1983  xiv, 683 p. ; 25 cm
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Table of Contents: Read more
Material Balances in Non-Reacting Processes
Species Balances in Reacting Systems
Element Balances
Material Balances in Process Flowsheets
Introduction to Energy Balances
Energy Balances for Nonreacting Systems
Energy Balances for Reacting Systems
Material and Energy Balances in Process Flowsheets
Appendixes
Material Balances in Non-Reacting Processes
Species Balances in Reacting Systems
Element Balances
23.

Book
Book
23. Mathematical programming via augmented lagrangians : an introduction with computer programs (: pbk)
Donald A. Pierre, Michael J. Lowe
Published: Reading, Mass. : Addison-Wesley Pub. Co., Advanced Book Program, 1975  xxi, 436 p. ; 25 cm
Series: Applied mathematics and computation / series editor Robert Kalaba ; no. 9
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24.

Book
Book
24. Applied nonlinear programming
David M. Himmelblau
Published: New York : McGraw-Hill, c1972  xi, 498 p. ; 23 cm
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25.

Book
Book
25. Introduction to sensitivity and stability analysis in nonlinear programming
Anthony V. Fiacco
Published: New York : Academic Press, 1983  xii, 367 p. ; 24 cm
Series: Mathematics in science and engineering : a series of monographs and textbooks ; v. 165
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26.

Book
Book
26. The Newton-Cauchy framework : a unified approach to unconstrained nonlinear minimization (: gw ; : us)
J.L. Nazareth
Published: Berlin ; New York : Springer-Verlag, c1994  xii, 101 p. ; 24 cm
Series: Lecture notes in computer science ; 769
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27.

Book
Book
27. Nonlinear programming : theory and algorithms. 2nd ed (: hard ; : pbk)
Mokhtar S. Bazaraa, Hanif D. Sherali, C.M. Shetty
Published: New York ; Chichester : Wiley, c1993  xiii, 638 p. ; 26 cm
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Table of Contents: Read more
Introduction. / Chapter 1：
Problem Statement and Basic Definitions / 1.1：
Illustrative Examples / 1.2：
Guidelines for Model Construction / 1.3：
Exercises
Notes and References
Convex Analysis. / Part 1：
Convex Sets. / Chapter 2：
Convex Hulls / 2.1：
Closure and Interior of a Set / 2.2：
Weierstrass's Theorem / 2.3：
Separation and Support of Sets / 2.4：
Convex Cones and Polarity / 2.5：
Polyhedral Sets, Extreme Points, and Extreme Directions / 2.6：
Linear Programming and the Simplex Method / 2.7：
Convex Functions and Generalizations. / Chapter 3：
Definitions and Basic Properties / 3.1：
Subgradients of Convex Functions / 3.2：
Differentiable Convex Functions / 3.3：
Minima and Maxima of Convex Functions / 3.4：
Generalizations of Convex Functions / 3.5：
Optimality Conditions and Duality. / Part 2：
The Fritz John and Karush-Kuhn-Tucker Optimality Conditions. / Chapter 4：
Unconstrained Problems / 4.1：
Problems Having Inequality Constraints / 4.2：
Problems Having Inequality and Equality Constraints / 4.3：
Second-Order Necessary and Sufficient Optimality Conditions for Constrained Problems / 4.4：
Constraint Qualifications. / Chapter 5：
Cone of Tangents / 5.1：
Other Constraint Qualifications / 5.2：
Lagrangian Duality and Saddle Point Optimality Conditions. / 5.3：
Lagrangian Dual Problem / 6.1：
Duality Theorems and Saddle Point Optimality Conditions / 6.2：
Properties of the Dual Function / 6.3：
Formulating and Solving the Dual Problem / 6.4：
Getting the Primal Solution / 6.5：
Linear and Quadratic Programs / 6.6：
Algorithms and Their Convergence / Part 3：
The Concept of an Algorithm. / Chapter 7：
Algorithms and Algorithmic Maps / 7.1：
Closed Maps and Convergence / 7.2：
Composition of Mappings / 7.3：
Comparison Among Algorithms / 7.4：
Unconstrained Optimization. / Chapter 8：
Line Search Without Using Derivatives / 8.1：
Line Search Using Derivatives / 8.2：
Some Practical Line Search Methods / 8.3：
Closedness of the Line Search Algorithmic Map / 8.4：
Multidimensional Search Without Using Derivatives / 8.5：
Multidimensional Search Using Derivatives / 8.6：
Modification of Newton's Method: Levenberg-Marquardt and Trust Region Methods / 8.7：
Methods Using Conjugate Directions: Quasi-Newton and Conjugate Gradient Methods / 8.8：
Subgradient Optimization Methods / 8.9：
Penalty and Barrier Functions. / Chapter 9：
Concept of Penalty Functions / 9.1：
Exterior Penalty Function Methods / 9.2：
Exact Absolute Value and Augmented Lagrangian Penalty Methods / 9.3：
Barrier Function Methods / 9.4：
Polynomial-Time Interior Point Algorithms for Linear Programming Based on a Barrier Function / 9.5：
Methods of Feasible Directions. / Chapter 10：
Method of Zoutendijk / 10.1：
Convergence Analysis of the Method of Zoutendijk / 10.2：
Successive Linear Programming Approach / 10.3：
Successive Quadratic Programming or Projected Lagrangian Approach / 10.4：
Gradient Projection Method of Rosen / 10.5：
Reduced Gradient Method of Wolfe and Generalized Reduced Gradient Method / 10.6：
Convex-Simplex Method of Zangwill / 10.7：
Effective First- and Second-Order Variants of the Reduced Gradient Method / 10.8：
Linear Complementary Problem, and Quadratic, Separable, Fractional, and Geometric Programming. / Chapter 11：
Linear Complementary Problem / 11.1：
Convex and Nonconvex Quadratic Programming: Global Optimization Approaches / 11.2：
Separable Programming / 11.3：
Linear Fractional Programming / 11.4：
Geometric Programming / 11.5：
Mathematical Review. / Appendix A：
Summary of Convexity, Optimality Conditions, and Duality. / Appendix B：
Bibliography.
Index
Introduction. / Chapter 1：
Problem Statement and Basic Definitions / 1.1：
Illustrative Examples / 1.2：
28.

Book
Book
28. Nonlinear programming theory and methods (: North-Holland ; : American Elsevier)
by Béla Martos
Published: Amsterdam : North-Holland Pub. Co. , New York : American Elsevier Pub. Co., 1975  279 p. ; 24 cm
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29.

Book
Book
29. The nonlinear workbook : chaos, fractals, cellular automata, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, fuzzy logic with C++, java and symbolicC++ programs. 6th ed (: hardcover ; : pbk)
Willi-Hans Steeb ; in collaboration with Yorick Hardy, Ruedi Stoop
Published: New Jersey : World Scientific, c2015  xx, 662 p. ; 24 cm
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30.

Book
Book
30. Global optimization using interval analysis. 2nd ed., rev. and expanded
Eldon Hansen, G. William Walster
Published: New York : M. Dekker, c2004  xvii, 489 p. ; 24 cm
Series: Monographs and textbooks in pure and applied mathematics ; 264
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31.

Book
Book
31. Linear and nonlinear programming : an introduction to linear methods in mathematical programming (: Ellis Horwood Limited - Library Edn. - : Halsted Press - Student Edn.)
Roger Hartley
Published: Chichester, West Sussex : E. Horwood , New York : Wiley, 1985  221 p. ; 23 cm
Series: Ellis Horwood series in mathematics and its applications
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32.

Book
Book
32. Recent advances in global optimization (: hard ; : pbk.)
Christodoulos A. Floudas and Panos M. Pardalos, editors
Published: Princeton, N.J. : Princeton University Press, c1992  x, 633 p. ; 24 cm
Series: Princeton series in computer science
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33.

Book
Book
33. Multilevel optimization : algorithms and applications
edited by Athanasios Migdalas, Panos M. Pardalos and Peter Värbrand
Published: Dordrecht ; Boston : Kluwer Academic Publishers, 1997  xxii, 384 p. ; 25 cm
Series: Nonconvex optimization and its applications ; v. 20
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34.

Book
Book
34. Optimization under constraints : theory and applications of nonlinear programming
Peter Whittle
Published: London ; New York : Wiley-Interscience, c1971  ix, 241 p. ; 24 cm
Series: Wiley series in probability and mathematical statistics
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35.

Book
Book
35. Theory of linear and non-linear programming
S. Vajda
Published: London : Longman, 1974  viii, 118 p. ; 22 cm
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36.

Book
Book
36. Selected applications of nonlinear programming
[by] Jerome Bracken and Garth P. McCormick
Published: New York : Wiley, c1968  xii, 110 p. ; 23 cm
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37.

eBook
ＥＢ
37. Nonlinear programming : theory and algorithms. 3rd ed (: electronic bk)
Mokhtar S. Bazaraa, Hanif D. Sherali, C.M. Shetty
Published: Wiley Online Library, 2005  1 online resource (xv, 853p)
Series: A Wiley-Interscience publication
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Table of Contents: Read more
Introduction. / Chapter 1：
Problem Statement and Basic Definitions / 1.1：
Illustrative Examples / 1.2：
Guidelines for Model Construction / 1.3：
Exercises
Notes and References
Convex Analysis. / Part 1：
Convex Sets. / Chapter 2：
Convex Hulls / 2.1：
Closure and Interior of a Set / 2.2：
Weierstrass's Theorem / 2.3：
Separation and Support of Sets / 2.4：
Convex Cones and Polarity / 2.5：
Polyhedral Sets, Extreme Points, and Extreme Directions / 2.6：
Linear Programming and the Simplex Method / 2.7：
Convex Functions and Generalizations. / Chapter 3：
Definitions and Basic Properties / 3.1：
Subgradients of Convex Functions / 3.2：
Differentiable Convex Functions / 3.3：
Minima and Maxima of Convex Functions / 3.4：
Generalizations of Convex Functions / 3.5：
Optimality Conditions and Duality. / Part 2：
The Fritz John and Karush-Kuhn-Tucker Optimality Conditions. / Chapter 4：
Unconstrained Problems / 4.1：
Problems Having Inequality Constraints / 4.2：
Problems Having Inequality and Equality Constraints / 4.3：
Second-Order Necessary and Sufficient Optimality Conditions for Constrained Problems / 4.4：
Constraint Qualifications. / Chapter 5：
Cone of Tangents / 5.1：
Other Constraint Qualifications / 5.2：
Lagrangian Duality and Saddle Point Optimality Conditions. / 5.3：
Lagrangian Dual Problem / 6.1：
Duality Theorems and Saddle Point Optimality Conditions / 6.2：
Properties of the Dual Function / 6.3：
Formulating and Solving the Dual Problem / 6.4：
Getting the Primal Solution / 6.5：
Linear and Quadratic Programs / 6.6：
Algorithms and Their Convergence / Part 3：
The Concept of an Algorithm. / Chapter 7：
Algorithms and Algorithmic Maps / 7.1：
Closed Maps and Convergence / 7.2：
Composition of Mappings / 7.3：
Comparison Among Algorithms / 7.4：
Unconstrained Optimization. / Chapter 8：
Line Search Without Using Derivatives / 8.1：
Line Search Using Derivatives / 8.2：
Some Practical Line Search Methods / 8.3：
Closedness of the Line Search Algorithmic Map / 8.4：
Multidimensional Search Without Using Derivatives / 8.5：
Multidimensional Search Using Derivatives / 8.6：
Modification of Newton's Method: Levenberg-Marquardt and Trust Region Methods / 8.7：
Methods Using Conjugate Directions: Quasi-Newton and Conjugate Gradient Methods / 8.8：
Subgradient Optimization Methods / 8.9：
Penalty and Barrier Functions. / Chapter 9：
Concept of Penalty Functions / 9.1：
Exterior Penalty Function Methods / 9.2：
Exact Absolute Value and Augmented Lagrangian Penalty Methods / 9.3：
Barrier Function Methods / 9.4：
Polynomial-Time Interior Point Algorithms for Linear Programming Based on a Barrier Function / 9.5：
Methods of Feasible Directions. / Chapter 10：
Method of Zoutendijk / 10.1：
Convergence Analysis of the Method of Zoutendijk / 10.2：
Successive Linear Programming Approach / 10.3：
Successive Quadratic Programming or Projected Lagrangian Approach / 10.4：
Gradient Projection Method of Rosen / 10.5：
Reduced Gradient Method of Wolfe and Generalized Reduced Gradient Method / 10.6：
Convex-Simplex Method of Zangwill / 10.7：
Effective First- and Second-Order Variants of the Reduced Gradient Method / 10.8：
Linear Complementary Problem, and Quadratic, Separable, Fractional, and Geometric Programming. / Chapter 11：
Linear Complementary Problem / 11.1：
Convex and Nonconvex Quadratic Programming: Global Optimization Approaches / 11.2：
Separable Programming / 11.3：
Linear Fractional Programming / 11.4：
Geometric Programming / 11.5：
Mathematical Review. / Appendix A：
Summary of Convexity, Optimality Conditions, and Duality. / Appendix B：
Bibliography.
Index
Introduction
Convex Analysis
Convex Sets
Convex Functions and Generalizations
Optimality Conditions and Duality
The Fritz John and Karush-Kuhn-Tucker Optimality Conditions
Constraint Qualification
Lagrangian Duality and Saddle Point Optimality Conditions
The Concept of an Algorithm
Unconstrained Optimization
Penalty and Barrier Functions
Methods of Feasible Directions
Linear Complementary Problem, and Quadratic, Separable, Fractional, and Geometric Programming
Mathematical Review
Summary of Convexity, Optimality Conditions, and Duality
Bibliography
Introduction. / Chapter 1：
Problem Statement and Basic Definitions / 1.1：
Illustrative Examples / 1.2：
38.

eBook
ＥＢ
38. Linear and nonlinear programming. 5th ed (: electronic bk)
David G. Luenberger, Yinyu Ye
Published: ProQuest Ebook Central  1 online resource (xv, 609 p.)
Series: International series in operations research & management science ; v. 228
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39.

Book
Book
39. Material and energy balances for engineers and environmentalists. 2nd ed
Colin Oloman
Published: London : World Scientific Publishing Europe, c2023  xxxii, 403 p. ; 25 cm
Series: Advances in Chemical and Process Engineering ; v. 3
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40.

Book
Book
40. Nonlinear programming. 3rd ed.
Dimitri P. Bertsekas
Published: Belmont, Mass. : Athena Scientific, c2016  xviii, 861 p. ; 24 cm
Series: Athena Scientific optimization and computation series ; 1
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