Abstract
In this chapter we first summarize how the optimal control and optimization problems in stochastic supply chain systems have been approached in this book and state the important managerial insights. Secondly, we point out the limitations of the methods presented in this book and indicate the directions for further research.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arruda, E.F., Do Val, J.B.R.: Stability and optimality of a multi-product production and storage system under demand uncertainty. Eur. J. Oper. Res. 188(2), 406–427 (2008)
Arshinder, K., Kanda, A., Deshmukh, S.G.: Supply chain coordination: perspectives, empirical studies and research directions. Int. J. Prod. Econ. 115(2), 316–335 (2008)
Benjaafar, S., ElHafsi, M., Lee, C.Y., Zhou, W.H.: Optimal control of an assembly system with multiple stages and multiple demand classes. Oper. Res. 59(2), 522–529 (2011)
Bertsekas, D.P., Tsitsiklis, J.N.: Neuro-Dynamic Programming. Athena Scientific, Belmont (1996)
Chaib-draa, B., Muller, J.P.: Multiagent-Based Supply Chain Management. Springer, Berlin (2006)
De Kok, A.G., Visschers, J.W.C.H.: Analysis of assembly systems with service level constraints. Int. J. Prod. Econ. 59(1–3), 313–326 (1999)
Elhedhli, S., Merrick, R.: Green supply chain network design to reduce carbon emissions. Transp. Res. Part D 17(5), 370–379 (2012)
Janakiraman, G., Muckstadt, J.A.: A decomposition approach for a class of capacitated serial systems. Oper. Res. 57(6), 1384–1393 (2009)
Min, H., Zhou, G.: Supply chain modeling: past, present and future. Comput. Ind. Eng. 43(1–2), 231–249 (2002)
Muharremoglu, A., Tsitsiklis, J.N.: A single-unit decomposition approach to multiechelon inventory systems. Oper. Res. 56, 1089–1103 (2008)
Powell, W.B.: Approximate Dynamic Programming: Solving the Curses of Dimensionality. Wiley, Hoboken (2007)
Sarimveis, H., Patrinos, P., Tarantilis, C., Kiranoudis, C.: Dynamic modeling and control of supply chain systems: a review. Comput. Oper. Res. 35(11), 3530–3561 (2008)
Si, J., Barto, A., Powell, W.B., Wunsch, D.: Learning and Approximate Dynamic Programming: Scaling up to the Real World. Wiley, New York (2004)
Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. The MIT Press, Cambridge (1998)
Wang, F., Lai, X., Shi, N.: A multi-objective optimization for green supply chain network design. Decis. Support Syst. 51(2), 262–269 (2011)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this chapter
Cite this chapter
Song, DP. (2013). Conclusions. In: Optimal Control and Optimization of Stochastic Supply Chain Systems. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-4724-4_15
Download citation
DOI: https://doi.org/10.1007/978-1-4471-4724-4_15
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-4723-7
Online ISBN: 978-1-4471-4724-4
eBook Packages: EngineeringEngineering (R0)