Algorithms (solution methods) are used for optimal decision making with multiple objectives in operations research, management science, economics, finance and engineering design. An optimal decision needs to take into consideration possible future uncertainties which, as they become known, result in a necessary revision of the decision and the consideration of new future uncertainties. This volume is study of this topic. It is a distillation of research in developing methodologies and reflects research in this area. The question of multiple objective decision making with a nonlinear static problem framework is considered using quadratic programming, nonlinear programming, nonlinear constrained min-max, mean-variance optimization and noncooperative Nash games.
Publisher: John Wiley and Sons Ltd
Number of pages: 320
Weight: 570 g
Dimensions: 235 x 155 x 22 mm
"This book is one of the most up-to-date, comprehensive and integrated treatments of nonlinear programming algorithms and multiple objective decisions...It is clearly one of those rare books that deals with a complex subject matter and yet is easy to read and comprehend." (Computational Statistics Data Analysis
"The book is mainly written for researchers...and computer scientists...Its strong points are in serving this community with a self-contained introduction into nonlinear programming tailored to needs for tackling multiple-objective decisions under uncertainty from the specific viewpoint adopted in the book." (Optima, Vol. 60, December 1998)