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170608 ||| eng |
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|a 9783319558103
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|a Mujica Mota, Miguel
|e [editor]
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| 245 |
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|a Applied Simulation and Optimization 2
|h Elektronische Ressource
|b New Applications in Logistics, Industrial and Aeronautical Practice
|c edited by Miguel Mujica Mota, Idalia Flores De La Mota
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2017, 2017
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| 300 |
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|a XIV, 282 p. 127 illus., 107 illus. in color
|b online resource
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| 505 |
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|a Preface -- Introduction -- Supply Chain Problems -- Logistics Problems -- Manufacturing Problems -- Aeronautical Problems -- Big Data Applications -- Conclusions -- Bibliography -- References
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| 653 |
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|a Industrial engineering
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| 653 |
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|a Engineering mathematics
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| 653 |
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|a Computer simulation
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| 653 |
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|a Computer Modelling
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| 653 |
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|a Mathematics / Data processing
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| 653 |
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|a Industrial and Production Engineering
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| 653 |
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|a Computational Science and Engineering
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| 653 |
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|a Engineering / Data processing
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| 653 |
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|a Mathematical and Computational Engineering Applications
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| 653 |
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|a Production engineering
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| 700 |
1 |
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|a Flores De La Mota, Idalia
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 028 |
5 |
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|a 10.1007/978-3-319-55810-3
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-319-55810-3?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 003.3
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| 520 |
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|a Building on the author’s earlier Applied Simulation and Optimization, this book presents novel methods for solving problems in industry, based on hybrid simulation-optimization approaches that combine the advantages of both paradigms. The book serves as a comprehensive guide to tackling scheduling, routing problems, resource allocations and other issues in industrial environments, the service industry, production processes, or supply chains and aviation. Logistics, manufacturing and operational problems can either be modelled using optimization techniques or approaches based on simulation methodologies. Optimization techniques have the advantage of performing efficiently when the problems are properly defined, but they are often developed through rigid representations that do not include or accurately represent the stochasticity inherent in real systems. Furthermore, important information is lost during the abstraction process to fit each problem into theoptimization technique. On the other hand, simulation approaches possess high description levels, but the optimization is generally performed through sampling of all the possible configurations of the system. The methods explored in this book are of use to researchers and practising engineers in fields ranging from supply chains to the aviation industry.
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