Computer Simulation in Management Science
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.
What people are saying - Write a review
We haven't found any reviews in the usual places.
Computer simulation in practice
12 other sections not shown
Other editions - View all
activity cycle diagram algorithm analyst arrival machine basic batch behaviour causal loop diagram Chapter computer program computer simulation consider defined delays detailed developed discrete event simulation discrete simulation display distribution DueNow effect entity equations event routine event-based example executive factors flow follows FORTRAN GPSS graphical harassed booking clerk Hence icons integer interval levels logic loop management science mean methods Micro Saint model logic negative exponential Normal distribution operation OR/MS organisations output personal enquirer phase phone call Pidd Poisson distribution possible problem structuring procedure produce programming language queue lengths random numbers recruitment regional warehouse response variables Section sequence shown in Figure shows simple SIMSCRIPT SIMSCRIPT II.5 simulation clock simulation language simulation model simulation program simulation software statistical Stella system dynamics task three-phase approach three-phase simulation TimeCell Turbo Pascal validation values variance variation VIMS visual interactive waiting