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Applied Probability Models with Optimization Applications

Applied Probability Models with Optimization Applications

Applied Probability Models with Optimization Applications
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Applied Probability Models with Optimization Applications Paperback - 1992

by Ross, Sheldon M

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Dover Publications, Incorporated. Used - Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Details

  • Title Applied Probability Models with Optimization Applications
  • Author Ross, Sheldon M
  • Binding Paperback
  • Edition Reprint
  • Condition Used - Very good
  • Pages 224
  • Volumes 1
  • Language ENG
  • Publisher Dover Publications, Incorporated, New York
  • Publication date 1992-12-04
  • Features Bibliography
  • Bookseller's Inventory # 595216-6
  • ISBN 9780486673141 / 0486673146
  • Weight 0.5 lbs (0.23 kg)
  • Dimensions 8.46 x 5.38 x 0.44 in (21.49 x 13.67 x 1.12 cm)
  • Category Mathematics
  • Library of Congress subjects Mathematical optimization, Probabilities
  • Library of Congress Catalogue Number 92016013
  • Dewey Decimal Code 519.2
  • Quantity available 1

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From the publisher

"A clarity of style and a conciseness of treatment which students will find most welcome. The material is valuable and well organized ... an excellent introduction to applied probability." -- Journal of the American Statistical Association.
This book offers a concise introduction to some of the stochastic processes that frequently arise in applied probability. Emphasis is on optimization models and methods, particularly in the area of decision processes. After reviewing some basic notions of probability theory and stochastic processes, the author presents a useful treatment of the Poisson process, including compound and nonhomogeneous Poisson processes. Subsequent chapters deal with such topics as renewal theory and Markov chains; semi-Markov, Markov renewal, and regenerative processes; inventory theory; and Brownian motion and continuous time optimization models.
Each chapter is followed by a section of useful problems that illustrate and complement the text. There is also a short list of relevant references at the end of every chapter. Students will find this a largely self-contained text that requires little previous knowledge of the subject. It is especially suited for a one-year course in applied probability at the advanced undergraduate or beginning postgraduate level. 1970 edition.

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