Heyman D.P., Sobel M.J. Handbook of Operation Research and Management Science Volume 2

Elsevier Science Publishers, 1990. - 723p.One of the central problems in operations research and management science
is how to quantify the effects of uncertainty about the future. This, the second
volume in a series of handbooks, is devoted to models where chance events
play a major role. The thirteen chapters survey topics in applied probability
that have been particularly useful in operations research and management
science. Each chapter was written by an expert (both in the subject matter and
in its exposition), and most are meant to be accessible at an introductory level.
By this we mean a calculus-based probability course and the rudiments of
matrix algebra.Stochastic models are concerned with phenomena that vary as time
advances, and where the variation has a significant chance component. Examples
in operations research and management science are legion. Two examples from
everyday life are the number of books on a library shelf and the availability of
the local copying machine. More intricate examples from commercial activities
are the stocks in the warehouse of a food chain and the availability of a
dialtone on your telephone.The chapters fall into four groups. The first four cover the fundamentals of
stochastic processes, and lay the foundation for the following chapters. The
next three chapters are concerned with methods of getting numbers. This
includes numerical solution of models, parameter estimation for models, and
simulation of models. Chapters 8 and 9 describe the fundamentals of dynamic
optimization. The last four chapters are concerned with the most important
structured models in operations research and management science; queues,
queueing networks, inventories, and reliability.