Linear Nonlilear Programming

For some considerable time, linear programming has been one of the methods of operations research which has been widely known and much applied in Germany too, both in the literature ofthe subject and in practice. Its applications range from production planning through finance planning and from optimization of traffic networks through urban planning. The literature of linear programming includes textbooks of a strictly mathematical nature as weil as programmed textbooks for those with no previous knowledge of mathematics. An objection frequently heard to more extensive dissemination of the theories of linear programming in the practical field has been that data wh ich are available in practice are at once too inexact and too unreliable to provide the basis for the application of "exact" procedures like linear programming.

Stochastic programming is a fast developing area of optimization and mathematical programming. Numerous papers and conference volumes, and several monographs have been published in the area; however, the Kall and Mayer book will be particularly useful in presenting solution methods including their solid theoretical basis and their computational issues, based in many cases on implementations by the authors. The book is also suitable for advanced courses in stochastic optimization.

The book is an introductory textbook mainly for students of computer science and mathematics. Our guiding phrase is "what every theoretical computer scientist should know about linear programming". A major focus is on applications of linear programming, both in practice and in theory. The book is concise, but at the same time, the main results are covered with complete proofs and in sufficient detail, ready for presentation in class.