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Stochastic Simulation Optimization : an Optimal Computing Budget Allocation.
With the advance of new computing technology, simulation is becoming very popular for designing large, complex, and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Singapore :
World Scientific,
2010.
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| Colección: | Stochastic Simulation Optimization.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Chen, Chun-Hung. | |
| 245 | 1 | 0 | |a Stochastic Simulation Optimization : |b an Optimal Computing Budget Allocation. |
| 260 | |a Singapore : |b World Scientific, |c 2010. | ||
| 300 | |a 1 online resource (248 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Stochastic Simulation Optimization | |
| 505 | 0 | |a Foreword; Preface; Acknowledgments; Contents; 1. Introduction to Stochastic Simulation Optimization; 2. Computing Budget Allocation; 3. Selecting the Best from a Set of Alternative Designs; 4. Numerical Implementation and Experiments; 5. Selecting An Optimal Subset; 6. Multi-objective Optimal Computing Budget Allocation; 7. Large-Scale Simulation and Optimization; 8. Generalized OCBA Framework and Other Related Methods; Appendix A: Fundamentals of Simulation; Appendix B: Basic Probability and Statistics; Appendix C: Some Proofs in Chapter 6; Appendix D: Some OCBA Source Codes; References. | |
| 520 | |a With the advance of new computing technology, simulation is becoming very popular for designing large, complex, and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be v. | ||
| 588 | 0 | |a Print version record. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Mathematical optimization. | |
| 650 | 0 | |a Stochastic processes. | |
| 650 | 0 | |a Systems engineering |x Simulation methods. | |
| 650 | 6 | |a Optimisation mathématique. | |
| 650 | 6 | |a Processus stochastiques. | |
| 650 | 6 | |a Ingénierie des systèmes |x Méthodes de simulation. | |
| 650 | 7 | |a Mathematical optimization |2 fast | |
| 650 | 7 | |a Stochastic processes |2 fast | |
| 700 | 1 | |a Lee, Loo Hay. | |
| 776 | 0 | 8 | |i Print version: |a Chen, Chun-Hung. |t Stochastic Simulation Optimization : An Optimal Computing Budget Allocation. |d Singapore : World Scientific, ©2010 |z 9789814282642 |
| 830 | 0 | |a Stochastic Simulation Optimization. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=731175 |z Texto completo |
| 938 | |a EBL - Ebook Library |b EBLB |n EBL731175 | ||
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