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1.

図書

図書
edited by Athanasios Migdalas, Panos M. Pardalos and Peter Värbrand
出版情報: Dordrecht ; Boston : Kluwer Academic Publishers, 1997  xxii, 384 p. ; 25 cm
シリーズ名: Nonconvex optimization and its applications ; v. 20
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2.

図書

図書
by Hoang Tuy
出版情報: Dordrecht : Kluwer Academic Publishers, c1998  xi, 339 p. ; 25 cm
シリーズ名: Nonconvex optimization and its applications ; v. 22
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3.

図書

図書
Eldon Hansen, G. William Walster
出版情報: New York : M. Dekker, c2004  xvii, 489 p. ; 24 cm
シリーズ名: Monographs and textbooks in pure and applied mathematics ; 264
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4.

図書

図書
P.M. Pardalos, J.B. Rosen
出版情報: Berlin ; Tokyo : Springer-Verlag, c1987  vii, 143 p. ; 25 cm
シリーズ名: Lecture notes in computer science ; 268
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5.

図書

図書
Anthony L. Peressini, Francis E. Sullivan, J. Jerry Uhl, Jr.
出版情報: New York ; Tokyo : Springer-Verlag, c1988  x, 273 p. ; 25 cm
シリーズ名: Undergraduate texts in mathematics
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目次情報: 続きを見る
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.

図書

図書
by Kenneth J. Arrow, Leonid Hurwicz, Hirofumi Uzawa ; with contributions by Hollis B. Chenery ... [et al.]
出版情報: Stanford, Calif. : Stanford University Press, 1958  229 p. ; 26 cm
シリーズ名: Stanford mathematical studies in the social sciences ; 2
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7.

図書

図書
editor, J. Abadie ; contributors, S. Vajda ... [et al.]
出版情報: Amsterdam : North-Holland, 1967  xxii, 316 p. ; 23 cm
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8.

図書

図書
Mordecai Avriel
出版情報: Englewood Cliffs, N.J. : Prentice-Hall, c1976  xv, 512 p. ; 24 cm
シリーズ名: Prentice-Hall series in automatic computation
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9.

図書

図書
Mokhtar S. Bazaraa, C.M. Shetty
出版情報: New York : Wiley, c1979  xiv, 560 p. ; 24 cm
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目次情報: 続きを見る
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:
10.

図書

図書
Immanuel M. Bomze ... [et al.]
出版情報: Dordrecht : Kluwer Academic Publishers, c1997  xi, 348 p. ; 25 cm
シリーズ名: Nonconvex optimization and its applications ; v. 18
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目次情報: 続きを見る
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:
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