Aggregate Planning Based on Stochastic Demand DEA Model With an Application in Production Planning

Gongbing BI, Kun XIANG

Abstract


Market demand and inventory are usually known in traditional DEA-based resource allocation method. However, market demand is always changing according to the market discipline. Thus, it is not rigorous to view market demand as constant. To cope with the uncertain demand, we further develop our mathematical model and impose the normality assumption for the stochastic product demands. In the end, a numerical example with hypothetical production data is used to illustrate the model.


Keywords


Production planning; Resource allocation; Data envelopment analysis (DEA); Stochastic demand

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References


Bertrand, J., & Rutten, W. (1999). Evaluation of three production planning procedures for the use of recipe flexibility. European Journal of Operational Research, 115(1), 179-194.

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.

Cooper, W., Huang, Z., & Li, S. X. (1996). Satisficing DEA models under chance constraints. Annals of Operations Research, 66(4), 279-295.

Du, J., Liang, L., Chen, Y., & Bi, G.-B. (2010). DEA-based production planning. Omega, 38(1), 105-112.

Fisher, M., Ramdas, K., & Zheng, Y.-S. (2001). Ending inventory valuation in multiperiod production scheduling. Management Science, 47(5), 679-692.

Gupta, A., & Maranas, C. D. (2000). A two-stage modeling and solution framework for multisite midterm planning under demand uncertainty. Industrial & Engineering Chemistry Research, 39(10), 3799-3813.

Gupta, A., & Maranas, C. D. (2003). Managing demand uncertainty in supply chain planning. Computers & Chemical Engineering, 27(8), 1219-1227.

Leung, S. C., Wu, Y., & Lai, K. (2003). Multi-site aggregate production planning with multiple objectives: A goal programming approach. Production Planning & Control, 14(5), 425-436.

Nahmias, S. (1989). Production and operations analysis. Irwin, Homewood, IL, 201-206.

Petkov, S. B., & Maranas, C. D. (1998). Design of single-product campaign batch plants under demand uncertainty. AIChE Journal, 44(4), 896-911.

Sodhi, M. S., & Tang, C. S. (2009). Modeling supply-chain planning under demand uncertainty using stochastic programming: A survey motivated by asset–liability management. International Journal of Production Economics, 121(2), 728-738.

Wellons, H. S., & Reklaitis, G. (1989). The design of multiproduct batch plants under uncertainty with staged expansion. Computers & Chemical Engineering, 13(1), 115-126.

Bi, G.-B., Mao, Q.-L., & Ding, J.-J. (2013). Dynamic resource allocation based on DEA with an application in production planning. Journal of University of Electronic Science and Technology of China, 5(15), 46-51.




DOI: http://dx.doi.org/10.3968/6054

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