Title :
Stochastic Linear Optimization for Modeling Uncertainty in Aggregate Production Planning
Author :
Yong-quan, Zhao ; Li-bin, LU ; Shu-fen, FANG
Author_Institution :
Harbin Inst. of Technol.
Abstract :
A stochastic linear optimization approach for studying demand uncertainty in the aggregate production planning problem is proposed. To realize the integrative decision of production planning and inventory policy, inventory variation in stochastic demand is analyzed, and the average inventory in planning periods is invited into the APP model. The planning output in every period is stochastic variables having the same distributions with the production demands. The approach is demonstrated in case of a Chinese automobile company sensitivity analysis shows the significant influence of production cycle and standard deviation on optimal reproduction point and the expected profit
Keywords :
aggregate planning; demand forecasting; inventory management; linear programming; stochastic processes; aggregate production planning; demand uncertainty; integrative decision; inventory policy; inventory variation; optimal reproduction; production cycle; sensitivity analysis; stochastic linear optimization; stochastic production demand; stochastic variable; uncertainty modeling; Aggregates; Automobiles; Costs; Manufacturing; Mathematical model; Optimized production technology; Production planning; Sensitivity analysis; Stochastic processes; Uncertainty;
Conference_Titel :
Autonomic and Autonomous Systems, 2006. ICAS '06. 2006 International Conference on
Conference_Location :
Silicon Valley, CA
Print_ISBN :
0-7695-2653-5
DOI :
10.1109/ICAS.2006.57