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Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics
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Markov Models & Optimization (Hardcover, Softcover Repri)
Loot Price: R5,779
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Markov Models & Optimization (Hardcover, Softcover Repri)
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Expected to ship within 10 - 15 working days
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This book presents a radically new approach to problems of
evaluating and optimizing the performance of continuous-time
stochastic systems. This approach is based on the use of a family
of Markov processes called Piecewise-Deterministic Processes (PDPs)
as a general class of stochastic system models. A PDP is a Markov
process that follows deterministic trajectories between random
jumps, the latter occurring either spontaneously, in a Poisson-like
fashion, or when the process hits the boundary of its state space.
This formulation includes an enormous variety of applied problems
in engineering, operations research, management science and
economics as special cases; examples include queueing systems,
stochastic scheduling, inventory control, resource allocation
problems, optimal planning of production or exploitation of
renewable or non-renewable resources, insurance analysis, fault
detection in process systems, and tracking of maneuvering targets,
among many others. The first part of the book shows how these
applications lead to the PDP as a system model, and the main
properties of PDPs are derived. There is particular emphasis on the
so-called extended generator of the process, which gives a general
method for calculating expectations and distributions of system
performance functions. The second half of the book is devoted to
control theory for PDPs, with a view to controlling PDP models for
optimal performance: characterizations are obtained of optimal
strategies both for continuously-acting controllers and for control
by intervention (impulse control). Throughout the book, modern
methods of stochastic analysis are used, but all the necessary
theory is developed from scratch and presented in a self-contained
way. The book will be useful to engineers and scientists in the
application areas as well as to mathematicians interested in
applications of stochastic analysis.
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