Numerical Optimization with Computational Errors - Volume 108

This book studies the approximate solutions of optimizationproblems in the presence of computational errors.

A number of results arepresented on the convergence behavior of algorithms in a Hilbert space;these algorithms are examined taking into account computational errors.

Theauthor illustrates that algorithms generate a good approximate solution, ifcomputational errors are bounded from above by a small positive constant.

Knowncomputational errors  are examined withthe aim of determining an approximate solution.

Researchers and students interestedin the optimization theory and its applications will find this book instructiveand informative.  This monograph contains 16 chapters; including a chapters devotedto the subgradient projection algorithm, the mirror descent algorithm, gradientprojection algorithm, the Weiszfelds method, constrained convex minimizationproblems, the convergence of a proximal point method in a Hilbert space, the continuoussubgradient method, penalty methods and Newton's method.