Enhanced descriptions from Syndetics:

Computer Simulation in Management Science Michael Pidd The Management School. University of Lancaster, UK The fourth edition of this book reflects its continued popularity and standing in the field. It provides a clear guide to the role of modelling in the computer simulation methods used in management science. Readers will find an in-depth coverage of the modelling, computing and statistical aspects of discrete simulation and systems dynamics. Part I is a general introduction to the simulation methods commonly used in management science. Part II gives a detailed exposition of discrete event simulation, and Part III provides a description of the methods of system dynamics as an approach to policy modelling within organisations. Overall, the book shows why computer simulation within organisations. Overall, the book shows why computer simulation models are popular and gives a thorough guide to their construction and use. Revisions to this edition include a completely new chapter on computer simulation in practice, which discusses how best to make use of computer simulation models in achieving real benefits within organisations. Updated areas include: *three-phase and other methods *sampling methods *output analysis and experimentation *discrete simulation software *system dynamics simulation There are also links to software libraries in Turbo Pascal, C, C++, Visual BASIC and Java on the World Wide Web.

Table of contents provided by Syndetics

• Preface to the Fifth Edition
• Part I Fundamentals Of Computer Simulation In Management Science
• 1 The computer simulation approach
• 1.1 Models, experiments and computers
• 1.2 Some applications of computer simulation
• 1.2.1 Manufacturing
• 1.2.2 Health care
• 1.2.3 Business process re-engineering
• 1.2.4 Transport systems
• 1.2.5 Defence
• 1.3 Models in management science
• 1.4 Simulation as experimentation
• 1.5 Why simulate?
• 1.5.1 Simulation versus direct experimentation
• 1.5.2 Simulation versus mathematical modelling
• 1.6 Summary
• Exercises
• References
• 2 A variety of modelling approaches
• 2.1 General considerations
• 2.2 Time handling
• 2.2.1 Time slicing
• 2.2.2 Next-event technique
• 2.2.3 Time slicing or next event?
• 2.3 Stochastic or deterministic?
• 2.3.1 Deterministic simulation: a time-slicing example
• 2.3.2 Stochastic simulation
• 2.4 Discrete or continuous change
• 2.4.1 Discrete change
• 2.4.2 Continuous change
• 2.4.3 A few words on simulation software
• Exercises
• References
• 3 Computer simulation in practice
• 3.1 Process, content, problem and project
• 3.1.1 Process and content
• 3.1.2 Problems and projects
• 3.1.3 Two parallel streams
• 3.2 The simulation problem part of the study
• 3.3 Problem structuring
• 3.3.1 Problem structuring as exploration
• 3.4 Modelling
• 3.4.1 Conceptual model building
• 3.4.2 Computer implementation
• 3.4.3 Validation
• 3.4.4 Experimentation
• 3.4.5 Implementation
• 3.5 The project part of the study
• 3.5.1 Initial negotiation and project definition
• 3.5.2 Project management and control
• 3.5.3 Project completion
• Exercises
• References
• 4 Static Monte Carlo simulation
• 4.1 Basic ideas
• 4.1.1 Risk and uncertainty
• 4.1.2 The replacement problem: a reprise
• 4.1.3 Static Monte Carlo simulation defined
• 4.2 Some important considerations
• 4.2.1 Subjective probabilities
• 4.2.2 Repeatability
• 4.3 Some simple static simulations
• 4.3.1 The loan repayment
• 4.3.2 An investment decision
• 4.4 Simulation on spreadsheets
• Exercises
• References
• Part II Discrete Event Simulation
• 5 Discrete event modelling
• 5.1 Fundamentals
• 5.2 Terminology
• 5.2.1 Objects of the system
• 5.2.2 The organization of entities
• 5.2.3 Operations of the entities
• 5.3 Activity cycle diagrams
• 5.3.1 Example 1: a simple job shop
• 5.3.2 Example 2: the harassed booking clerk
• 5.3.3 Example 3: the delivery depot
• 5.3.4 Using the activity cycle diagram
• 5.4 Activity cycle diagrams: a caveat
• Exercises
• References
• 6 How discrete simulation software works
• 6.1 Introduction
• 6.1.1 Why understand how simulation software is organized?
• 6.1.2 Simulation executives in more detail
• 6.1.3 Application logic
• 6.2 The three-phase approach
• 6.2.1 Bs
• 6.2.2 Cs
• 6.2.3 The exception to the general rule
• 6.2.4 Bs and Cs in the harassed booking clerk problem
• 6.2.5 Another example: a T-junction
• 6.3 How the three-phase approach works
• 6.3.1 The A phase
• 6.3.2 The B phase
• 6.3.3 The C phase
• 6.4 The harassed booking clerk--a manual three-phase simulation
• 6.4.1 The first A phase
• 6.4.2 The first B phase
• 6.4.3 The first C phase
• 6.4.4 The second A phase
• 6.4.5 The next B and C phases
• 6.4.6 The third A phase
• 6.4

Author notes provided by Syndetics