DocumentCode :
3020465
Title :
A Credibility-Based Fuzzy Programming Model for APP Problem
Author :
Zhu, Haiping ; Zhang, Jian
Author_Institution :
State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
1
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
455
Lastpage :
459
Abstract :
We analyze the importance of practical aggregate production planning (APP) under uncertain environment and present a novel fuzzy programming resolution model based on the credibility measure of fuzzy event. The customers´ demands, the unit profits and the available manufacturing capacities are all regarded as fuzzy variables; three types of common constraints are re-formulated as fuzzy chance constraints. Considering that the generalized fuzzy optimizing model is difficult to solve, we deduce an equivalent transformation technique on the assumption that the fuzzy variables obey trapezoidal distributions. In this way we convert these models into a equivalent crisp linear programming model which can be rapidly solved by the Simplex algorithm. Finally, we employ this approach on a real-world fuzzy APP problem in an automobile pressing company. The results demonstrate the effectiveness and applicability of the proposed algorithm.
Keywords :
aggregate planning; fuzzy set theory; linear programming; Simplex algorithm; aggregate production planning; automobile pressing company; credibility based fuzzy programming; fuzzy variables; linear programming model; transformation technique; Aggregates; Costs; Linear programming; Manufacturing; Mathematical programming; Mathematics; Optimization methods; Optimized production technology; Production planning; Weight measurement; aggregate production planning; credibility theory; fuzzy programming; fuzzy set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.204
Filename :
5376264
Link To Document :
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