DocumentCode :
2405962
Title :
Online parameter optimization for a multi-product, multi-machine manufacturing system
Author :
Dhingra, Jastej S. ; Blankenship, Gilmer L.
Author_Institution :
Syst. Res. Center, Maryland Univ., College Park, MD, USA
fYear :
1992
fDate :
1992
Firstpage :
1676
Abstract :
The authors develop an algorithm based on infinitesimal perturbation analysis for online optimization of a multiproduct service facility composed of a network of multiserver machines, modeled using multiclass M/M/m queues. Starting from the Robbins-Monro stochastic approximation method, they first develop an online, local optimization algorithm for a single multiserver machine. For the special case of Poisson arrivals and exponentially distributed service times in a multimachine network, local optimization at individual machines leads to global optimization of the overall network. Simulation results for a single machine are compared to the exact analytical results. The application of the methodology for optimization of a simple flexible manufacturing system is also presented
Keywords :
flexible manufacturing systems; perturbation techniques; production control; queueing theory; Poisson arrivals; Robbins-Monro stochastic approximation method; exponentially distributed service times; flexible manufacturing system; global optimization; infinitesimal perturbation analysis; local optimization algorithm; multi-machine manufacturing system; multiclass M/M/m queues; multiproduct service facility; multiserver machines; Algorithm design and analysis; Analytical models; Approximation algorithms; Approximation methods; Control systems; Cost function; Educational institutions; Flexible manufacturing systems; Manufacturing systems; Optimization methods; Queueing analysis; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-0872-7
Type :
conf
DOI :
10.1109/CDC.1992.371144
Filename :
371144
Link To Document :
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