Title :
Stochastic optimization algorithms for marketing-production manufacturing systems
Author :
Yin, G. ; Yan, H. ; Zhang, Q. ; Boukas, E.K.
Author_Institution :
Dept. of Math., Wayne State Univ., Detroit, MI, USA
fDate :
6/21/1905 12:00:00 AM
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 of convergence algorithms
Keywords :
advertising; approximation theory; finite difference methods; optimal control; optimisation; production control; constrained stochastic approximation procedure; marketing-production manufacturing systems; random demand; random directions finite difference methods; rate of convergence; stochastic machine capacity; stochastic optimization algorithms; Convergence; Cost function; Manufacturing systems; Mathematics; Optimal control; Production; Pulp manufacturing; Stochastic processes; Stochastic systems; Systems engineering and theory;
Conference_Titel :
Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
Print_ISBN :
0-7803-5250-5
DOI :
10.1109/CDC.1999.832911
