Robust Discrete Optimization and Its Applications

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

This text deals with decision-making in environments of significant data uncertainty, with particular emphasis on operations and production management applications. For such environments, this text suggests the use of the robustness approach to decision making, which assumes inadequate knowledge of the decision-maker about the random state of nature and develops a decision that hedges against the worst contingency that may arize. The book provides a comprehensive mathematical programming framework for robust decision making. It also presents decision support tools and solution methods for generating robust decisions in a variety of interesting application environments such as: linear programming; assignment problems; shortest paths; minimum spanning trees; knapsack problems; resource allocation; scheduling; production planning; location; inventory; layout planning; network design; and international sourcing.