Title :
Robust optimization model for fan coil production planning under supply uncertainty
Author :
Nazemi, Jamshid ; Zakeri, Roja
Author_Institution :
Dept. of Ind. Eng., Islamic Azad Univ., Tehran, Iran
Abstract :
Optimal Production and capacity planning problems have been one of major operation management concerns researches. The model parameter´s challenge effect on the solution has caused most of these practices unreliable. In this research we have considered a Heating, Ventilation and Air Conditioning (HVAC) production planning problem utilizing a supply base network. Proposed optimization model considered three uncertainty parameters of products lead time, machine efficiency and contractor collaboration mechanism. Objective function is minimizing costs of final product and its related parts with over 470 items. Proposed robust stochastic programming model, utilized a scenario approach to handle uncertainty of mentioned parameters. Through combination of three uncertain parameters 27 scenarios produced. Considering scenarios and its related probability, we have analyzed robustness of model. As proposed model has been used for problem with large number of variables and constraints, its framework can be used for similar production planning problems in other industries.
Keywords :
HVAC; capacity planning (manufacturing); probability; production planning; stochastic programming; uncertainty handling; contractor collaboration mechanism; fan coil production planning; heating ventilation air conditioning production planning problem; operation management; optimal capacity planning problems; optimal production planning problem; optimization model; robust optimization model; robust stochastic programming model; supply uncertainty; Coils; Optimization; Production planning; Programming; Robustness; Stochastic processes; Uncertainty; Production planning; Robust modeling; Robust optimization; Robust solution; Scenario optimizations; Stochastic programming;
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4577-0740-7
Electronic_ISBN :
2157-3611
DOI :
10.1109/IEEM.2011.6117940