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Product DescriptionCOMPREHENSIVE 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. Many realistic problems cannot be adequately represented as a linear program owing to the nature of the nonlinearity of the objective function and/or the nonlinearity of any constraints. The Third Edition begins with a general introduction to nonlinear programming with illustrative examples and guidelines for model construction. Concentration on the three major parts of nonlinear programming is provided:
- Convex analysis with discussion of topological properties of convex sets, separation and support of convex sets, polyhedral sets, extreme points and extreme directions of polyhedral sets, and linear programming
- Optimality conditions and duality with coverage of the nature, interpretation, and value of the classical Fritz John (FJ) and the Karush-Kuhn-Tucker (KKT) optimality conditions; the interrelationships between various proposed constraint qualifications; and Lagrangian duality and saddle point optimality conditions
- Algorithms and their convergence, with a presentation of algorithms for solving both unconstrained and constrained nonlinear programming problems
- New topics such as second interior point methods, nonconvex optimization, nondifferentiable optimization, and more
- Updated discussion and new applications in each chapter
- Detailed numerical examples and graphical illustrations
- Essential coverage of modeling and formulating nonlinear programs
- Simple numerical problems
- Advanced theoretical exercises
From the PublisherPresents recent developments of key topics in nonlinear programming using a logical and self-contained format. Divided into three sections that deal with convex analysis, optimality conditions and duality, computational techniques. Precise statements of algorithms are given along with convergence analysis. Each chapter contains detailed numerical examples, graphical illustrations and numerous exercises to aid readers in understanding the concepts and methods discussed. --This text refers to an out of print or unavailable edition of this title.
From the Back CoverCOMPREHENSIVE 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. Many realistic problems cannot be adequately represented as a linear program owing to the nature of the nonlinearity of the objective function and/or the nonlinearity of any constraints. The Third Edition begins with a general introduction to nonlinear programming with illustrative examples and guidelines for model construction. Concentration on the three major parts of nonlinear programming is provided:
- Convex analysis with discussion of topological properties of convex sets, separation and support of convex sets, polyhedral sets, extreme points and extreme directions of polyhedral sets, and linear programming
- Optimality conditions and duality with coverage of the nature, interpretation, and value of the classical Fritz John (FJ) and the Karush-Kuhn-Tucker (KKT) optimality conditions; the interrelationships between various proposed constraint qualifications; and Lagrangian duality and saddle point optimality conditions
- Algorithms and their convergence, with a presentation of algorithms for solving both unconstrained and constrained nonlinear programming problems
- New topics such as second interior point methods, nonconvex optimization, nondifferentiable optimization, and more
- Updated discussion and new applications in each chapter
- Detailed numerical examples and graphical illustrations
- Essential coverage of modeling and formulating nonlinear programs
- Simple numerical problems
- Advanced theoretical exercises
About the AuthorMokhtar S. BAZARAA, PhD, is a Professor at the Georgia Institute of Technology. HANIF D. SHERALI, PhD, is a W. Thomas Rice Chaired Professor of Engineering in the Grado Department of Industrial and Systems Engineering at Virginia Polytechnic Institute and State University. C. M. SHETTY, PhD, is a Professor Emeritus at the Georgia Institute of Technology.
Professors Bazaraa and Sherali are also coauthors of the complementary bestselling book, Linear Programming and Network Flows, Third Edition, also published by Wiley.
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