Computer Simulation in Management Science

The 5th edition of this popular book is essential for management science students, MBAs and practitioners in this area. It shows how practical simulation models are built and used, and provides the theory needed to do this – whatever software is used. It covers the modelling methods, computing and statistical requirements for successful simulation and includes:a new chapter on Monte Carlo simulation using spreadsheets
a new look inside discrete simulation software
simulation models in Visual Basic, SIMUL8 and Micro Saint
system dynamics using Powersim

Spis treści:
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 structu ring.
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 phas e.
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.
6.4.7 The third B phase.
6.5 The event–based worldview.
6.5.1 Events in the harassed booking clerk problem.
6.5.2 Event–based executives.
6.6 The activity–scanning approach.0
6.6.1 Activities.
6.6.2 Activity–scanning executives.
6.7 Process–based approaches.
6.7.1 Processes in the harassed booking clerk problem.
6.7.2 Process interaction.
6.7.3 Process–based executives.
6.8 Which approach is best?
6.8.1 Three–phase versus process–based approaches.
Exercises.
References.
7 Writing a three–phase simulation program.
7.1 Introduction.
7.1.1 The basic structure of the library.
7.2 Inside the executive.
7.2.1 The control array.
7.2.2 Using the control array to operate a three–phase simulation.
7.3 The Visual Basic implementation.
7.3.1 Some comments on Visual Basic.
7.3.2 The variables and their types.
7.3.3 The A phase.
7.3.4 The B phase.
7.3.5 The C phase.
7.3.6 Running the simulation.
7.4 Using VBSim to simulate the harassed booking clerk problem.
7.4.1 Entities, Bs and Cs.
7.4.2 Personal enquirers and phone calls arrive.
7.4.3 The end of personal service and phone calls.
7.4.4 Observations.
7.4.5 The Cs.
7.4.6 Initialization and finalization.
7.5 Putting it all together.
Exercises.
References.
8 Visual interactive modelling and simulation.
8.1 Basic ideas.
8.1.1 Visual interactive modelling (VIM).
8.1.2 Visual simulation output.
8.1.3 Interaction.
8.1.4 A caveat.
8.2 Designing a visual simulation display.
8.2.1 Iconic displays.
8.2.2 Logical displays.
8.2.3 Chart displays.
8.3 VIMS.
8.3.1 Joe’s exhaust parlour.
8.3.2 Joe’s exhaust parlour in Micro Saint: model building.
8.3.3 Joe 217;s exhaust parlour in Micro Saint: running and analysing the simulation.
8.3.4 Joe’s exhaust parlour in SIMUL8: model building.
8.3.5 Joe’s exhaust parlour in SIMUL8: running and analysing the simulation.
8.4 Visual interactive simulation: a reprise.
Exercises.
References.
9 Discrete simulation software.
9.1 General principals.
9.2 A quick overview of discrete simulation software.
9.3 VIMS and their relatives.
9.3.1 VIMSEa reprise.
9.3.2 Block diagram systems.
9.3.3 VIMS and block diagram systems.
9.4 Programming using a general purpose language.
9.4.1 Pros and cons.
9.4.2 Libraries and component–based software.
9.5 Programming approaches using simulation languages.
9.5.1 Common features of simulation languages.
9.5.2 An example: SIMSCRIPT II.5.
9.6 Layered systems and application templates.
9.6.1 Layered systems.
9.6.2 Application templates.
9.7 Appraising simulation software: some principles.
9.7.1 The type of application.
9.7.2 The expectations for end use.
9.7.3 Knowledge, computing policy and user support.
9.7.4 Price.
9.8 Which to choose? Horses for courses.
9.8.1 VIMS.
9.8.2 Simulation languages.
References.
10 Sampling methods.
10.1 Basic ideas.
10.1.1 General principles of random sampling.
10.1.2 Top–hat sampling.
10.1.3 The fundamental random sampling process.
10.1.4 Use of pre–written libraries of algorithms.
10.2 Random number generation.
10.2.1 Truly random numbers.
10.2.2 Pseudo–random numbers.
10.2.3 Congruential generators.
10.2.4 General requirements for these generators.
10.2.5 Multiplicative congruential generators.
10.2.6 Improving on simple congruential generators.
10.2.7 Using inbuilt random number generators.
10.3 Testing random number generators.
10.3.1 Scatter plots.
10.3.2 Auxiliary sequences.
10.3.3 Frequency tests.
10.3.4 Serial test.
10.