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Convex majorization with an application to the length of critical paths

Published online by Cambridge University Press:  14 July 2016

Isaac Meilijson*
Affiliation:
Tel-Aviv University
Arthur Nádas*
Affiliation:
IBM System Products Division
*
Postal address: Department of Statistics, Tel-Aviv University, Ramat-Aviv, Tel-Aviv, Israel.
∗∗ Postal address: IBM System Products Division, Hopewell Junction, NY 12575, U.S.A.

Abstract

  1. 1. (Y) for all non-negative, non-decreasing convex functions φ (X is convexly smaller than Y) if and only if, for all .

  2. 2. Let H be the Hardy–Littlewood maximal function HY(x) = E(Y – X | Y > x). Then HY(Y) is the smallest random variable exceeding stochastically all random variables convexly smaller than Y.

  3. 3. Let X1X2 · ·· Xn be random variables with given marginal distributions, let I1,I2, ···, Ik be arbitrary non-empty subsets of {1,2, ···, n} and let M = max (M is the completion time of a PERT network with paths Ij, and delay times Xi.) The paper introduces a computation of the convex supremum of M in the class of all joint distributions of the Xi's with specified marginals, and of the ‘bottleneck probability' of each path.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1979 

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Footnotes

Research carried out while this author was Visiting Scientist at the IBM Thomas J. Watson Research Center, Yorktown Heights.

References

[1] Dubins, L. E. and Meilijson, I. (1974) On stability for optimization problems. Ann. Prob. 2, 243255.Google Scholar
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[4] Lai, T. L. and Robbins, H. E. (1977) A class of dependent random variables and their maxima.Google Scholar
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[6] Robillard, P. and Trahan, M. (1977) The completion time of PERT networks. Opns Res. 25, 1529.Google Scholar