By V. V. Kolbin (auth.), R. V. Gamkrelidze (eds.)
ISBN-10: 1468433091
ISBN-13: 9781468433098
ISBN-10: 1468433113
ISBN-13: 9781468433111
This quantity includes overview articles: "Stochastic seasoned gramming" by way of Vo V. Kolbin, and "Application of Queueing-Theoretic tools in Operations study, " by way of N. Po Buslenko and A. P. Cherenkovo the 1st article covers just about all points of stochastic programming. a few of the effects provided in it haven't pre viously been surveyed within the Soviet literature and are of curiosity to either mathematicians and economists. the second one article com prises an exhaustive treatise at the current cutting-edge of the statistical equipment of queueing concept and the statistical modeling of queueing platforms as utilized to the research of advanced structures. Contents STOCHASTIC PROGRAMMING V. V. Kolbin creation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 § 1. The Geometry of Stochastic Linear Programming difficulties. . . . . . . . . . . . . . . . . . . . five § 2. Chance-Constrained difficulties . . . . . . . . . eight § three. Rigorous assertion of stochastic Linear Programming difficulties . . . . . . . . . . sixteen § four. Game-Theoretic assertion of Stochastic Linear Programming difficulties. . . . . . . . 18 § five. Nonrigorous assertion of SLP difficulties . . . 19 § 6. life of domain names of balance of the recommendations of SLP difficulties . . . . . . . . . 29 § 7. balance of an answer within the suggest. . . . . . . . . . . . 30 § eight. twin Stochastic Linear Programming difficulties. . . 37 § nine. a few Algorithms for the answer of Stochastic Linear Programming difficulties . . . . . . . . . . forty § 10. Stochastic Nonlinear Programming: a few First effects . . . . . . . . . . . . . . . . . . . . . . forty two § eleven. The Two-Stage SNLP challenge. . . . . . . . . . . . forty seven § 12. Optimality and lifestyles of a Plan in Stochastic Nonlinear Programming difficulties. fifty eight Literature mentioned . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Additional resources for Progress in Mathematics: Probability Theory, Mathematical Statistics, and Theoretical Cybernetics
Example text
The convex hull of the pOints (a11' g (au) and (ai2' g (ad) is a segment connecting these two points. The segment, by the convexity of the function g (xi)' is the upper boundary and is determined by the equation If r == 2, then, depending on the position of the random vector x E I, it is necessary to consider two cases, for each of which H3 is bounded above by two hyperplanes. A more precise upper estimate for the expected value of the function g(xi' x2, ... , x r) is obtained if fuller use is made of the convexity of g (x).
E. This proves the theorem. 7) Pl(Q)X 1 +PZX2 + ... +PnxnO; j=1,2, ... ,n. The elements of the column P1 (q) are independent random variables a11 (q), a21 (q) •... , amI (q). 7) have a unique optimal plan in the mean x* (~ with positive component (~. Arbuzov proposes the change xi =~; Yz = ~; ... Yn =.!!!.... 7) transforms to the linear-fractional programming problem of variables y = q; (x); YI max c, -BYI + c,112 ~ + PIYc + ... + PnYn <;: - y __ + (nLl.!!... 8) = 1,2, ... , fl. 8) the column of free terms of the system of constraints is random.
Let the vector x* be such that min EC (b (q), x)=EC (b (q), x*) x and let the vectors x*(q) be such that min C (b (q), x)=C (b (q), x* (q». x Then C (b (q), x*) ::> C (b (q), x*(q» for any q. Hence, EC (b (q), x*) > >- EC (b (q), x* (q», which yields on the basis of the notation introduced above min EC (b (q), x) >- E min C (b (q), x). 29) we consider for any q the dual of the problem min C (b (q), x). Let the functional of x the dual problem be b (q)T z. If z* (q) is the optimal solution of this 28 V.
Progress in Mathematics: Probability Theory, Mathematical Statistics, and Theoretical Cybernetics by V. V. Kolbin (auth.), R. V. Gamkrelidze (eds.)
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