A computational framework for learning production planning policies

IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management

Volumn , Issue , 2009, Pages 1087-1091

  Narasimhamurthy, Srinivas ^a   Muni, Durga Prasad ^a  

^a INFOSYS TECHNOLOGIES LTD   (India)

Author keywords

Markov decision process; Production planning

Indexed keywords

COMPUTATIONAL FRAMEWORK; CONSUMER GOODS; CONSUMER PACKAGED GOODS; LEARNING FRAMEWORKS; MARKOV DECISION PROCESSES; PROBLEM FORMULATION; PRODUCTION MODES; PRODUCTION PLANNING; PRODUCTION QUANTITY; SIMULATION-BASED;

INDUSTRIAL ENGINEERING; MARKOV PROCESSES; PRODUCTION CONTROL; PRODUCTION ENGINEERING; PROJECT MANAGEMENT;

PLANNING;

EID: 77949521746     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEEM.2009.5372948     Document Type: Conference Paper

References (6)

1. D. Bertsekas and J. Tsitsiklis, Neuro-dynamic programming, Athena Scientific, Belmont, MA, 1996.
2. G.R. Bitran, E. Haas, and H. Matsuo, "Production planning of style goods with high setup costs and forecast revisions", Operations Research 34(2), 1986, 226-236.
3. A. George and W.B. Powell, "Adaptive stepsizes for recursive estimation with applications in approximate dynamic programming", Machine Learning 65(1),2006, 167-198.
4. M.L. Puterman,Markov Decision Processes, John Wiley and Sons, New York, 1994.
5. R. Sutton and A. Barto, Reinforcement Learning, The MIT Press, Cambridge, Massachusetts, 1998.
6. B. Van Roy, D. Bertsekas, Y. Lee and J. Tsitsiklis, "A neuro-dynamic programming approach to retailer inventory management", Proceedings of the IEEE Conference on Decision and Control, Vol 4, 1997, 4052-4057.