DocumentCode :
2964984
Title :
A computational framework for learning production planning policies
Author :
Narasimhamurthy, Sai ; Muni, D.P.
Author_Institution :
SET Labs., Infosys Technol. Ltd., Bangalore, India
fYear :
2009
fDate :
8-11 Dec. 2009
Firstpage :
1087
Lastpage :
1091
Abstract :
In a variety of production settings in industries such as consumer packaged goods (CPG), pharma and other consumer goods, a number of related items are produced together in the same production mode. The production of these families require setup of capacities, which can incur significant costs in terms of labor, material, etc. Hence production planners are faced with the challenge of determining production quantities and the sequence of changeovers so as to achieve an optimal long-term cost-containment strategy. In this paper, we detail the problem formulation and a simulation based policy learning framework. We also discuss the results of our computations performed using this framework.
Keywords :
Markov processes; production planning; Markov decision process; consumer packaged goods; cost-containment strategy; policies; policy learning framework; production planning; production quantities; Computational modeling; Computer industry; Cost function; Function approximation; Machinery production industries; Packaging; Process planning; Production planning; Sampling methods; Strategic planning; Markov Decision Process; Production planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4869-2
Electronic_ISBN :
978-1-4244-4870-8
Type :
conf
DOI :
10.1109/IEEM.2009.5372948
Filename :
5372948
Link To Document :
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