Guide to Computational Modelling for Decision Processes: Theory, Algorithms, Techniques and Applications

ISBN-13: 9783319856544 / Angielski / Miękka / 2018 / 396 str.

Berry, Stuart

Opis

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.

Spis treści

Part I: Introduction to Modelling and Model Evaluation

Model Building
Val Lowndes, Stuart Berry, Marcello Trovati, and Amanda Whitbrook

Introduction to Cellular Automata in Simulation
Val Lowndes, Adrian Bird, and Stuart Berry

Introduction to Mathematical Programming
Val Lowndes and Stuart Berry

Heuristic Techniques in Optimisation
Val Lowndes and Stuart Berry

Introduction to the Use of Queueing Theory and Simulation
Val Lowndes and Stuart Berry

Part II: Case Studies

Case Studies: Using Heuristics
Val Lowndes, Ovidiu Bagdasar, and Stuart Berry

Further Use of Heuristic Methods
Val Lowndes, Stuart Berry, Chris Parkes, Ovidiu Bagdasar, and Nicolae Popovici

Air Traffic Controllers Planning: A Rostering Problem
Richard Conniss

Solving Multiple Objective Problems: Modelling Diet Problems
Val Lowndes and Stuart Berry

Fuzzy Scheduling Applied to Small Manufacturing Firms
Val Lowndes

The Design and Optimisation of Surround Sound Decoders Using Heuristic Methods
B. Wiggins, Stuart Berry, and Val Lowndes

System Dynamics Case Studies
Chris Parkes, Stuart Berry, and John Stubbs

Applying Queueing Theory to the Design of a Traffic Light Controller
James Hardy

Cellular Automata and Agents in Simulations
Kim Smith, Richard Hill, Stuart Berry, and Richard Conniss

Three Big Data Case Studies
Marcello Trovati and Andy Baker

Part III: Appendices

Appendix A: Queueing Theory
Stuart Berry

Appendix B: Function Optimisation Techniques: Genetic Algorithms and Tabu Searches
Val Lowndes and Mirko Paskota

Appendix C: What to Simulate to Evaluate Production Planning and Control Methods in Small Manufacturing Firms
Stuart Berry and Val Lowndes

Appendix D: Defining Boolean and Fuzzy Logic Operators
Val Lowndes, Marcello Trovati, and Stuart Berry

Appendix E: Assessing the Reinstated Waverley Line
Stuart Berry and John Stubbs

Appendix F: Matching Services with Users in Opportunistic Network Environments
Stuart Berry

O autorze

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.

Blurb

This interdisciplinary reference and guide provides an introduction to modelling 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 modelling methods and tools, including heuristic and mathematical programming-based models, and queuing 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 queuing theory
• Reviews examples incorporating system dynamics modelling, cellular automata and agent-based simulations, and the use of big data
• Contains appendices covering queuing theory, function optimization techniques, Boolean and fuzzy logic, and transport modelling
• Describes simulation for the evaluation of production planning and control methods, and a model for matching services with users in opportunistic network environments

Researchers, practitioners and students in computer science, engineering and business studies will find this work to be an invaluable and in-depth introduction to the use of simulation techniques in the analysis of large and complex problems, in addition to providing an exhaustive description of the theoretical framework and applications being developed to address such problems.