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Hybrid Simulation Models of Production Networks / by Vassilis S. Kouikoglou, Yannis A. Phillis
版 | 1st ed. 2001. |
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出版者 | New York, NY : Springer US : Imprint: Springer |
出版年 | 2001 |
本文言語 | 英語 |
大きさ | XII, 196 p : online resource |
著者標目 | *Kouikoglou, Vassilis S author Phillis, Yannis A author SpringerLink (Online service) |
件 名 | LCSH:Mathematical models LCSH:Mathematical optimization LCSH:Calculus of variations LCSH:System theory LCSH:Control theory LCSH:Production management LCSH:Mechanical engineering FREE:Mathematical Modeling and Industrial Mathematics FREE:Calculus of Variations and Optimization FREE:Systems Theory, Control FREE:Operations Management FREE:Mechanical Engineering |
一般注記 | 1. Introduction -- 2. Fundamentals of Simulation Modeling -- 3. Two-Machine Systems -- 4. Production Lines -- 5. Production Networks -- 6. Optimization -- 7. Closure -- References -- Appendix A: Statistical Tables Industrial production is one of the most basic human activities indispensable to the economic activity. Due to its complexity, production is not very well understood and modeled as opposed to traditional fields of inquiry such as physics. This book aims at enhancing rigorous understanding of a particular area of production, that of analysis and optimization of production lines and networks using discrete event models and simulation. To our knowledge, this is the first book treating this subject from the point of view mentioned above. We have arrived at the realization that discrete event models and simulation provide perhaps the best tools to model production lines and networks for a number of reasons. Analysis is precise but demands enormous computational resources, usually unavailable in practical situations. Brute force simulation is also precise but slow when quick decisions are to be made. Approximate analytical models are fast but often unreliable as far as accuracy is concerned. The approach of the book, on the other hand, combines speed and accuracy to an exceptional degree in most practical applications HTTP:URL=https://doi.org/10.1007/978-1-4757-5438-4 |
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Springer eBooks | 9781475754384 |
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EB00232200 |
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