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This interdisciplinary reference and guide provides an introduction to modeling methodologies and models which form the starting point for deriving efficient and effective solution techniques, and presents a series of case studies that demonstrate how heuristic and analytical approaches may be used to solve large and complex problems. Topics and features: introduces the key modeling methods and tools, including heuristic and mathematical programming-based models, and queueing theory and simulation techniques; demonstrates the use of heuristic methods to not only solve complex decision-making problems, but also to derive a simpler solution technique; presents case studies on a broad range of applications that make use of techniques from genetic algorithms and fuzzy logic, tabu search, and queueing theory; reviews examples incorporating system dynamics modeling, cellular automata and agent-based simulations, and the use of big data; supplies expanded descriptions and examples in the appendices.
| Serija: | Simulation Foundations, Methods and Applications |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2017 |
| Knygos puslapių skaičius: | 408 |
| ISBN-10: | 3319554166 |
| ISBN-13: | 9783319554167 |
| Formatas: | 241 x 160 x 26 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Guide to Computational Modelling for Decision Processes: Theory, Algorithms, Techniques and Applications“
