Editors:
- Introduces modelling methodologies and models to enable the derivation of efficient and effective ways to produce good solutions
- Presents a series of case studies demonstrating how heuristic and analytical approaches may be used to solve large and complex problems
- Includes appendices covering queuing theory, function optimisation techniques, simulation for evaluation of PP&C systems, Boolean and fuzzy logic, transport modelling, and opportunistic networks
- Includes supplementary material: sn.pub/extras
Part of the book series: Simulation Foundations, Methods and Applications (SFMA)
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Table of contents (21 chapters)
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Front Matter
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Introduction to Modelling and Model Evaluation
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Front Matter
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Case Studies
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Front Matter
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Appendices
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Front Matter
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About this book
Editors and Affiliations
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Department of Computing and Mathematics, College of Engineering and Technology, University of Derby, Derby, United Kingdom
Stuart Berry
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University of Derby, Derby, United Kingdom
Val Lowndes, Marcello Trovati
About the editors
Dr. Stuart Berry is a lecturer in the Department of Computing and Mathematics at the University of Derby, UK. Dr. Marcello Trovati is a Senior Lecturer at the same institution. He is also a co-editor of the Springer titles Guide to Security Assurance for Cloud Computing and Big-Data Analytics and Cloud Computing. Val Lowndes is a Chartered Mathematician, who formerly worked at the University of Derby.
Bibliographic Information
Book Title: Guide to Computational Modelling for Decision Processes
Book Subtitle: Theory, Algorithms, Techniques and Applications
Editors: Stuart Berry, Val Lowndes, Marcello Trovati
Series Title: Simulation Foundations, Methods and Applications
DOI: https://doi.org/10.1007/978-3-319-55417-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-55416-7Published: 25 April 2017
Softcover ISBN: 978-3-319-85654-4Published: 09 May 2018
eBook ISBN: 978-3-319-55417-4Published: 13 April 2017
Series ISSN: 2195-2817
Series E-ISSN: 2195-2825
Edition Number: 1
Number of Pages: XII, 396
Number of Illustrations: 69 b/w illustrations, 101 illustrations in colour
Topics: Simulation and Modeling, Algorithm Analysis and Problem Complexity, Operations Research/Decision Theory, Mathematics of Algorithmic Complexity, Probability and Statistics in Computer Science