Dual-Feasible Functions for Integer Programming and Combinatorial Optimization
Dual-Feasible Functions for Integer Programming and Combinatorial Optimization: Basics, Extensions and Applications
Springer | Operations Research & Decision Theory | February 24, 2016 | ISBN-10: 3319276026 | 159 pages | pdf | 2.1 mb
Springer | Operations Research & Decision Theory | February 24, 2016 | ISBN-10: 3319276026 | 159 pages | pdf | 2.1 mb
Authors: Alves, C., Clautiaux, F., de Carvalho, J.V., Rietz, J.
Explains the concept of dual-feasible functions within the general framework of duality, Dantzig-Wolfe decomposition and column generation
Details relevant extensions and applications of dual-feasible functions to different combinatorial optimization problems
Provides a comprehensive set of illustrative examples to clarify the essential concepts, properties, and the main ideas behind recent extensions
This book provides a postgraduate audience the keys they need to understand and further develop a set of tools for the efficient computation of lower bounds and valid inequalities in integer programs and combinatorial optimization problems. After discussing the classical approaches described in the literature, the book addresses how to extend these tools to other non-standard formulations that may be applied to a broad set of applications. Examples are provided to illustrate the underlying concepts and to pave the way for future contributions.
Number of Illustrations and Tables
38 in colour
Topics
Operation Research/Decision Theory
Operations Research, Mathematical Programming
Discrete Optimization
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