Discrete optimization with interval data: minmax regret and fuzzy approach

The minmax regret approach to discrete optimization with interval data has attracted considerable attention in the recent decade. This book summarizes the state of the art in the area and addresses some open problems. Furthermore, itcontains a chapter devoted to the extension of the framework to the case whenfuzzy intervals are applied to model uncertain data. The fuzzy intervals allow a more sophisticated uncertainty evaluation in the setting of possibility theory. This book is a valuable source of information for all operations research practitioners who are interested in modern approaches to problem solving. Apart from the description of the theoretical framework, it also presents some algorithms that can be applied to solve problems that arise in practice. Novel research results in the field of Discrete Optimization with Interval Data Presents a new approach (robust optimization) to modeling incomplete knowledge INDICE: Part I Minmax regret combinatorial optimization problems with interval data.- Problem formulation.- Evaluation of optimality of solutions and elements.- Exact algorithms.- Approximation algorithms.- Minmax regret minimum selecting items.- Minmax regret minimum spanning tree.- Minmax regret shortest path.- Minmax regret minimum assignment.- Minmax regret minimum s - t cut.- Fuzzy combinatorial optimization problem.- Conclusions and open problems.- Part II Minmax regret sequencing problems with interval data.- Problem formulation.- Sequencing problem with maximum lateness criterion.- Sequencing problem withweighted number of late jobs.- Sequencing problem with the total flow time criterion.- Conclusions and open problems.

• ISBN: 978-3-540-78483-8
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 220
• Fecha Publicación: 01/04/2008
• Nº Volúmenes: 1
• Idioma: Inglés