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This Handbook is a collection of chapters on key issues in the
design and analysis of computer simulation experiments on models of
stochastic systems. The chapters are tightly focused and written by
experts in each area. For the purpose of this volume "simulation"
refers to the analysis of stochastic processes through the
generation of sample paths (realization) of the processes.
Attention focuses on design and analysis issues and the goal of
this volume is to survey the concepts, principles, tools and
techniques that underlie the theory and practice of stochastic
simulation design and analysis. Emphasis is placed on the ideas and
methods that are likely to remain an intrinsic part of the
foundation of the field for the foreseeable future. The chapters
provide up-to-date references for both the simulation researcher
and the advanced simulation user, but they do not constitute an
introductory level 'how to' guide.
Computer scientists, financial analysts, industrial engineers,
management scientists, operations researchers and many other
professionals use stochastic simulation to design, understand and
improve communications, financial, manufacturing, logistics, and
service systems. A theme that runs throughout these diverse
applications is the need to evaluate system performance in the face
of uncertainty, including uncertainty in user load, interest rates,
demand for product, availability of goods, cost of transportation
and equipment failures.
* Tightly focused chapters written by experts
* Surveys concepts, principles, tools, and techniques that underlie
the theory and practice of stochastic simulation design and
analysis
* Provides an up-to-date reference for bothsimulation researchers
and advanced simulation users
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