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

Important features of the Third Edition include:

• 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

The book is a solid reference for professionals as well as a useful text for students in the fields of ope...