Stochastic optimization algorithms for marketing-production manufacturing systems

G. Yin; H. Yan; Q. Zhang; E. K. Boukas

doi:10.1109/CDC.1999.832911

Stochastic optimization algorithms for marketing-production manufacturing systems

G. Yin
, H. Yan
, Q. Zhang
, E. K. Boukas

Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal

Abstract

We develop a class of stochastic optimization algorithms for marketing-production systems. The system includes random demand and stochastic machine capacity; the algorithm is a constrained stochastic approximation procedure that uses random directions finite difference methods. Under fairly general conditions, we obtain convergence and rate convergence algorithm.

Original language	English
Pages (from-to)	925-930
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	1
DOIs	https://doi.org/10.1109/CDC.1999.832911
Publication status	Published - 1999
Externally published	Yes
Event	The 38th IEEE Conference on Decision and Control (CDC) - Phoenix, AZ, USA Duration: 7 Dec 1999 → 10 Dec 1999

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SDG 9 Industry, Innovation, and Infrastructure

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10.1109/CDC.1999.832911

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@article{0d92e8c007ee4f0c96f23e08d4145f52,

title = "Stochastic optimization algorithms for marketing-production manufacturing systems",

abstract = "We develop a class of stochastic optimization algorithms for marketing-production systems. The system includes random demand and stochastic machine capacity; the algorithm is a constrained stochastic approximation procedure that uses random directions finite difference methods. Under fairly general conditions, we obtain convergence and rate convergence algorithm.",

author = "G. Yin and H. Yan and Q. Zhang and Boukas, \{E. K.\}",

year = "1999",

doi = "10.1109/CDC.1999.832911",

language = "English",

volume = "1",

pages = "925--930",

journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0191-2216",

publisher = "IEEE",

note = "The 38th IEEE Conference on Decision and Control (CDC) ; Conference date: 07-12-1999 Through 10-12-1999",

}

TY - JOUR

T1 - Stochastic optimization algorithms for marketing-production manufacturing systems

AU - Yin, G.

AU - Yan, H.

AU - Zhang, Q.

AU - Boukas, E. K.

PY - 1999

Y1 - 1999

N2 - We develop a class of stochastic optimization algorithms for marketing-production systems. The system includes random demand and stochastic machine capacity; the algorithm is a constrained stochastic approximation procedure that uses random directions finite difference methods. Under fairly general conditions, we obtain convergence and rate convergence algorithm.

AB - We develop a class of stochastic optimization algorithms for marketing-production systems. The system includes random demand and stochastic machine capacity; the algorithm is a constrained stochastic approximation procedure that uses random directions finite difference methods. Under fairly general conditions, we obtain convergence and rate convergence algorithm.

UR - https://www.scopus.com/pages/publications/0033343127

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0033343127&origin=recordpage

U2 - 10.1109/CDC.1999.832911

DO - 10.1109/CDC.1999.832911

M3 - RGC 22 - Publication in policy or professional journal

SN - 0191-2216

VL - 1

SP - 925

EP - 930

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

T2 - The 38th IEEE Conference on Decision and Control (CDC)

Y2 - 7 December 1999 through 10 December 1999

ER -

Stochastic optimization algorithms for marketing-production manufacturing systems

Abstract

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