{"product_id":"nonlinear-programming-9780471486008","title":"Nonlinear Programming","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eCOMPREHENSIVE COVERAGE OF NONLINEAR PROGRAMMING THEORY AND ALGORITHMS, THOROUGHLY REVISED AND EXPANDED   Nonlinear Programming: Theory and Algorithms-now in an extensively updated Third Edition-addresses the problem of optimizing an objective function in the presence of equality and inequality constraints.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"The promotional message on the back cover proclaims 'this book is a solid reference for professionals and a useful text for students…\"; and I fully agree.\" (\u003ci\u003eTechnometrics\u003c\/i\u003e, February 2007)  \u003cp\u003e\"Noted and recommended for its logical format and sharp editing that never wavers in its focus.\" (\u003ci\u003eElectric Review\u003c\/i\u003e, September\/October 2006)\u003c\/p\u003e \u003cp\u003e\"…highly recommended for a course in the theory of nonlinear programming…\" (\u003ci\u003eMAA Reviews\u003c\/i\u003e, July 17, 2006)\u003c\/p\u003e \u003cp\u003e ‘… ‘the Bazaraa’ is a must if you are interested in optimization…’ (\u003ci\u003eJournal of the Operational Research Society,\u003c\/i\u003e 2007)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eChapter 1 Introduction.\u003c\/b\u003e  \u003cp\u003e1.1 Problem Statement and Basic Definitions.\u003c\/p\u003e \u003cp\u003e1.2 Illustrative Examples.\u003c\/p\u003e \u003cp\u003e1.3 Guidelines for Model Construction.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1 Convex Analysis.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Convex Sets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Convex Hulls.\u003c\/p\u003e \u003cp\u003e2.2 Closure and Interior of a Set.\u003c\/p\u003e \u003cp\u003e2.3 Weierstrass's Theorem.\u003c\/p\u003e \u003cp\u003e2.4 Separation and Support of Sets.\u003c\/p\u003e \u003cp\u003e2.5 Convex Cones and Polarity.\u003c\/p\u003e \u003cp\u003e2.6 Polyhedral Sets, Extreme Points, and Extreme Directions.\u003c\/p\u003e \u003cp\u003e2.7 Linear Programming and the Simplex Method.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Convex Functions and Generalizations.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Definitions and Basic Properties.\u003c\/p\u003e \u003cp\u003e3.2 Subgradients of Convex Functions.\u003c\/p\u003e \u003cp\u003e3.3 Differentiable Convex Functions.\u003c\/p\u003e \u003cp\u003e3.4 Minima and Maxima of Convex Functions.\u003c\/p\u003e \u003cp\u003e3.5 Generalizations of Convex Functions.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2 Optimality Conditions and Duality.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 The Fritz John and Karush-Kuhn-Tucker Optimality Conditions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Unconstrained Problems.\u003c\/p\u003e \u003cp\u003e4.2 Problems Having Inequality Constraints.\u003c\/p\u003e \u003cp\u003e4.3 Problems Having Inequality and Equality Constraints.\u003c\/p\u003e \u003cp\u003e4.4 Second-Order Necessary and Sufficient Optimality Conditions for Constrained Problems.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Constraint Qualifications.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Cone of Tangents.\u003c\/p\u003e \u003cp\u003e5.2 Other Constraint Qualifications.\u003c\/p\u003e \u003cp\u003e5.3 Problems Having Inequality and Equality Constraints.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Lagrangian Duality and Saddle Point Optimality Conditions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Lagrangian Dual Problem.\u003c\/p\u003e \u003cp\u003e6.2 Duality Theorems and Saddle Point Optimality Conditions.\u003c\/p\u003e \u003cp\u003e6.3 Properties of the Dual Function.\u003c\/p\u003e \u003cp\u003e6.4 Formulating and Solving the Dual Problem\u003c\/p\u003e \u003cp\u003e6.5 Getting the Primal Solution.\u003c\/p\u003e \u003cp\u003e6.6 Linear and Quadratic Programs.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003ePart 3 Algorithms and Their Convergence.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 The Concept of an Algorithm.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Algorithms and Algorithmic Maps.\u003c\/p\u003e \u003cp\u003e7.2 Closed Maps and Convergence.\u003c\/p\u003e \u003cp\u003e7.3 Composition of Mappings.\u003c\/p\u003e \u003cp\u003e7.4 Comparison Among Algorithms.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Unconstrained Optimization.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Line Search Without Using Derivatives.\u003c\/p\u003e \u003cp\u003e8.2 Line Search Using Derivatives.\u003c\/p\u003e \u003cp\u003e8.3 Some Practical Line Search Methods.\u003c\/p\u003e \u003cp\u003e8.4 Closedness of the Line Search Algorithmic Map.\u003c\/p\u003e \u003cp\u003e8.5 Multidimensional Search Without Using Derivatives.\u003c\/p\u003e \u003cp\u003e8.6 Multidimensional Search Using Derivatives.\u003c\/p\u003e \u003cp\u003e8.7 Modification of Newton's Method: Levenberg-Marquardt and Trust Region Methods.\u003c\/p\u003e \u003cp\u003e8.8 Methods Using Conjugate Directions: Quasi-Newton and Conjugate Gradient Methods.\u003c\/p\u003e \u003cp\u003e8.9 Subgradient Optimization Methods.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Penalty and Barrier Functions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Concept of Penalty Functions.\u003c\/p\u003e \u003cp\u003e9.2 Exterior Penalty Function Methods.\u003c\/p\u003e \u003cp\u003e9.3 Exact Absolute Value and Augmented Lagrangian Penalty Methods.\u003c\/p\u003e \u003cp\u003e9.4 Barrier Function Methods.\u003c\/p\u003e \u003cp\u003e9.5 Polynomial-Time Interior Point Algorithms for Linear Programming Based on a Barrier Function.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Methods of Feasible Directions.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Method of Zoutendijk.\u003c\/p\u003e \u003cp\u003e10.2 Convergence Analysis of the Method of Zoutendijk.\u003c\/p\u003e \u003cp\u003e10.3 Successive Linear Programming Approach.\u003c\/p\u003e \u003cp\u003e10.4 Successive Quadratic Programming or Projected Lagrangian Approach.\u003c\/p\u003e \u003cp\u003e10.5 Gradient Projection Method of Rosen.\u003c\/p\u003e \u003cp\u003e10.6 Reduced Gradient Method of Wolfe and Generalized Reduced Gradient Method.\u003c\/p\u003e \u003cp\u003e10.7 Convex-Simplex Method of Zangwill.\u003c\/p\u003e \u003cp\u003e10.8 Effective First- and Second-Order Variants of the Reduced Gradient Method.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Linear Complementary Problem, and Quadratic, Separable, Fractional, and Geometric Programming.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Linear Complementary Problem.\u003c\/p\u003e \u003cp\u003e11.2 Convex and Nonconvex Quadratic Programming: Global Optimization Approaches.\u003c\/p\u003e \u003cp\u003e11.3 Separable Programming.\u003c\/p\u003e \u003cp\u003e11.4 Linear Fractional Programming.\u003c\/p\u003e \u003cp\u003e11.5 Geometric Programming.\u003c\/p\u003e \u003cp\u003eExercises.\u003c\/p\u003e \u003cp\u003eNotes and References.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A Mathematical Review.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B Summary of Convexity, Optimality Conditions, and Duality.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eBibliography.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex.\u003c\/b\u003e\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402608353623,"sku":"9780471486008","price":130.45,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780471486008.jpg?v=1730480945","url":"https:\/\/bookcurl.com\/products\/nonlinear-programming-9780471486008","provider":"Book Curl","version":"1.0","type":"link"}