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The application of engineering principles in divergent fields such
as management science and communications as well as the advancement
of several approaches in theory and computation have led to growing
interest in queueing models, creating the need for a comprehensive
text. Emphasizing Markovian structures and the techniques that
occur in different models, A Course on Queueing Models discusses
recent developments in the field, different methodological tools -
some of which are not available elsewhere - and computational
techniques. While most books essentially address the classical
methods of queueing theory, this text covers a broad range of
methods both in theory and in computation. The first part of the
textbook exposes you to many fundamental concepts at an
introductory level and provides tools for practitioners. It
discusses the basics in queueing theory for Markovian and
regenerative non-Markovian models, statistical inference,
simulation and some computational procedures, network and
discrete-time queues, algebraic and combinatorial methods, and
optimization. The second part delves deeper into the topics
examined in the first part by presenting more advanced methods.
This part also includes general queues, duality in queues, and
recent advancements on computational methods and discrete-time
queues. Each chapter contains a discussion section that summarizes
material and highlights special features. Incorporating different
queueing models, A Course on Queueing Models achieves an ideal
balance between theory and practice, making it compatible for
advanced undergraduate and graduate students, applied
statisticians, and engineers.
The application of engineering principles in divergent fields such
as management science and communications as well as the advancement
of several approaches in theory and computation have led to growing
interest in queueing models, creating the need for a comprehensive
text. Emphasizing Markovian structures and the techniques that
occur in different models, A Course on Queueing Models discusses
recent developments in the field, different methodological tools -
some of which are not available elsewhere - and computational
techniques. While most books essentially address the classical
methods of queueing theory, this text covers a broad range of
methods both in theory and in computation. The first part of the
textbook exposes you to many fundamental concepts at an
introductory level and provides tools for practitioners. It
discusses the basics in queueing theory for Markovian and
regenerative non-Markovian models, statistical inference,
simulation and some computational procedures, network and
discrete-time queues, algebraic and combinatorial methods, and
optimization. The second part delves deeper into the topics
examined in the first part by presenting more advanced methods.
This part also includes general queues, duality in queues, and
recent advancements on computational methods and discrete-time
queues. Each chapter contains a discussion section that summarizes
material and highlights special features. Incorporating different
queueing models, A Course on Queueing Models achieves an ideal
balance between theory and practice, making it compatible for
advanced undergraduate and graduate students, applied
statisticians, and engineers.
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