A coherent introduction to the techniques for modeling dynamic
stochastic systems, this volume also offers a guide to the
mathematical, numerical, and simulation tools of systems analysis.
Suitable for advanced undergraduates and graduate-level industrial
engineers and management science majors, it proposes modeling
systems in terms of their simulation, regardless of whether
simulation is employed for analysis.
Beginning with a view of the conditions that permit a
mathematical-numerical analysis, the text explores Poisson and
renewal processes, Markov chains in discrete and continuous time,
semi-Markov processes, and queuing processes. Each chapter opens
with an illustrative case study, and comprehensive presentations
include formulation of models, determination of parameters,
analysis, and interpretation of results. Programming
language-independent algorithms appear for all simulation and
numerical procedures. Solutions to the exercises are available upon
request from the publisher at
[email protected].
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