Nonlinear Programming: Theory and Algorithms

Nonlinear
Programming: Theory and Algorithms





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
operations research, management science, industrial engineering, applied
mathematics, and also in engineering disciplines that deal with
analytical optimization techniques. The logical and self-contained
format uniquely covers nonlinear programming techniques with a great
depth of information and an abundance of valuable examples and
illustrations that showcase the most current advances in nonlinear
problems.