Last edited by Tosar
Thursday, July 23, 2020 | History

4 edition of Stochastic models in operations research found in the catalog.

Stochastic models in operations research

by Daniel P. Heyman

  • 380 Want to read
  • 10 Currently reading

Published by McGraw-Hill in New York, London .
Written in English

    Subjects:
  • Operations research.,
  • Stochastic processes.

  • Edition Notes

    StatementDaniel P. Heyman, Matthew J. Sobel. Vol.2, Stochastic optimization.
    SeriesMcGraw-Hill series in quantitative methods for management
    ContributionsSobel, Matthew J.
    The Physical Object
    Paginationxv,555p. :
    Number of Pages555
    ID Numbers
    Open LibraryOL22445486M
    ISBN 100070286329

    A set of selected models in operations research and management science is applied here to show the various problems of real-life applications. In theory the decision-maker (DM) is supposed to know the type of model to apply in a given situation, also its parameters and the constraints of the environment. Introduction to Stochastic Processes - Lecture Notes (with 33 illustrations) is mostly the case when we model the waiting time until the first occurence of an event which may or may not ever happen. If it never happens, we will be waiting forever, and.

    Title: Stochastic Models in Operations Research Author: Heyman, Daniel P./ Sobel, Matthew J. Publisher: Dover Pubns Publication Date: /12/10 Number of Pages: Binding Type: PAPERBACK Library of Congress: Writing for graduate students dealing with stochastic processes in a range of fields (such as operations research, management. The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to 5/5(1).

    Additional Physical Format: Online version: Heyman, Daniel P. Stochastic models in operations research. New York: McGraw-Hill, ©© (OCoLC) A probabilistic study of the stochastic recurrence equation X_t=A_tX_{t-1}+B_t for real- and matrix-valued random variables A_t, where (A_t,B_t) constitute an iid sequence, is provided. The classical theory for these equations, including the existence and uniqueness of a stationary solution, the tail behavior with special emphasis on power law.


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