Résumé
The use of computers in decision support has grown
tremendously over the past five years. This book focuses on
uncertainty in computer programming, a cutting-edge area
which draws on fuzzy logic, genetic algorithms, neural
networks, and empirical data to analyze complex situations
such as those arising in the stock market. The book offers a
much-needed, essential guide to the use of uncertainty in
decision support systems and operations research as well as
in computer science, mathematics, and engineering.
tremendously over the past five years. This book focuses on
uncertainty in computer programming, a cutting-edge area
which draws on fuzzy logic, genetic algorithms, neural
networks, and empirical data to analyze complex situations
such as those arising in the stock market. The book offers a
much-needed, essential guide to the use of uncertainty in
decision support systems and operations research as well as
in computer science, mathematics, and engineering.
Table of contents
- Introduction to Mathematical Programming.
- Genetic Algorithms.
- Stochastic Simulation and Fuzzy Simulation.
- Expected Value Models.
- Chance-Constrained Programming.
- Applications of Chance-Constrained Programming.
- Dependent-Chance Programming.
- Modeling Stochastic Decision Systems.
- Chance-Constrained Programming with Fuzzy
Coefficients.
- Dependent-Chance Programming in Fuzzy
Environments.
- Fuzzy Programming with Fuzzy Decisions.
- Minimax Chance-Constrained Programming Models.
- Outline of Uncertain Programming.
- Appendix.
- Bibliography.
- List of Frequently Used Symbols.
- Index.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Wiley |
| Auteur(s) | Baoding Liu |
| Parution | 10/06/1999 |
| Nb. de pages | 250 |
| Format | 16 x 24 |
| Poids | 500g |
| EAN13 | 9780471359944 |
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