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Discrete Optimization with Interval Data Minmax Regret and Fuzzy Approach /
In operations research applications we are often faced with the problem of incomplete or uncertain data. This book considers solving combinatorial optimization problems with imprecise data modeled by intervals and fuzzy intervals. It focuses on some basic and traditional problems, such as minimum sp...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2008.
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| Edición: | 1st ed. 2008. |
| Colección: | Studies in Fuzziness and Soft Computing,
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| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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
- Minmax Regret Sequencing Problems with Interval Data
- Problem Formulation
- Sequencing Problem with Maximum Lateness Criterion
- Sequencing Problem with Weighted Number of Late Jobs
- Sequencing Problem with the Total Flow Time Criterion
- Conclusions and Open Problems
- Discrete Scenario Representation of Uncertainty.