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Algorithms for Nonlinear Programming and Multiple-Objective Decisions

Algorithms for Nonlinear Programming and Multiple-Objective Decisions

Berç Rustem

ISBN: 978-0-470-85959-9

Apr 1998

320 pages

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Algorithms are solution methods used for optimal decision making in mathematics and operations research. This book is a study of algorithms for decision making with multiple objectives. It is a distillation of recent research in developing methodologies for solving optimal decision problems in economics, and engineering and reflects current research in these areas.
Optimization of a Single Objective;
Quadratic Programming Algorithms;
Interactive Search for Acceptable Decisions: Updating Quadratic Objective Weights, Updating Bliss Points and Arbitrariness of Shadow Prices, Convergence and Complexity of Decision Processes;
Nonlinear Optimization with Convex Constraints: The Goldstein-Levitin-Polyak Algorithm;
Nonlinear Optimization with Equality and Inequality Constraints;
Convergence Rates of SQP Algorithms;
Algorithms for Equilibria and Games;
Mean Versus Variance Optimization: The Multi-Currency Portfolio;
The Nonlinear Case;
Uncertainty with Multiple Scenarios: Discrete Min-Max Algorithm for Equality Constraints.
"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)