This book discusses both the theory and applications of Markov chains.
The author studies both discrete-time and continuous-time chains and
connected topics such as finite Gibbs fields, non-homogeneous Markov
chains, discrete time regenerative processes, Monte Carlo simulation,
simulated annealing, and queueing networks are also developed in this
accessible and self-contained text. The text is firstly an introduction
to the theory of stochastic processes at the undergraduate or beginning
graduate level. Its primary objective is to initiate the student to the
art of stochastic modelling. The treatment is mathematical, with
definitions, theorems, proofs and a number of classroom examples which
help the student to fully grasp the content of the main results.
Problems of varying difficulty are proposed at the close of each
chapter. The text is motivated by significant applications and
progressively brings the student to the borders of contemporary
research. Students and researchers in operations research and electrical
engineering as well as in physics, biology and the social sciences will
find this book of interest.