DocumentCode :
3502326
Title :
An Approach for Production Planning Optimization Under Correlated Uncertain Demand
Author :
Chen, Huan-biao ; Zhao, Na ; Sun, Guang-qi
Author_Institution :
Transp. & Logistic Coll., Dalian Maritime Univ., Dalian
fYear :
2007
fDate :
21-25 Sept. 2007
Firstpage :
3736
Lastpage :
3739
Abstract :
Production planning optimization is one of the most important issues for manufactures and scholars. Production is planned to meet the future demand. Under the uncertainty of demand, profit is maximized and opportunity loss is minimized. In real case, however, the demands of products are usually correlated. Hence, in this paper, a method is proposed for production planning optimization under the correlated and uncertainty demand. Correlated random numbers are introduced to Monte Carlo simulation to meet the real case. The production planning is multi-objective, thus genetic algorithm is employed. In order to search the optimal solutions effectively and efficiently, GENOCOP system is utilized to initialize population. The algorithm is tested on real data, and a wonderful performance is shown.
Keywords :
Monte Carlo methods; production planning; Monte Carlo simulation; correlated random numbers; correlated uncertain demand; genetic algorithm; production planning optimization; Costs; Equations; Genetic algorithms; Logistics; Manufacturing; Marketing and sales; Production planning; Sun; Transportation; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1311-9
Type :
conf
DOI :
10.1109/WICOM.2007.924
Filename :
4340699
Link To Document :
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