DocumentCode :
3430015
Title :
An integrated supply chain model with fuzzy demand and its algorithm
Author :
Yuying ; Zhangwei
Author_Institution :
Coll. of Econ. & Manage., Southeast Univ., Nanjing
fYear :
2008
fDate :
7-10 April 2008
Firstpage :
1
Lastpage :
5
Abstract :
An integrated supply chain model with fuzzy demand is built in this paper. The model is converted into a bilevel programming, in which the upper level programming is an uncertain programming with fuzzy demand, and the lower level programming is a certain programming with the specified parameters passed from the upper level. A genetic algorithm combined with fuzzy simulation technology is proposed to find the optimal decisions in the upper level programming. In the lower level, under the given decision from the upper level, a simulated annealing algorithm is provided to obtain the optimal values which are then sent back to the upper level. Through the evolutionary processes such as crossover and mutation operations, the optimal solutions to achieve the minimum system cost can be found. Lastly numerical examples are given to show the validity of the algorithm.
Keywords :
fuzzy set theory; genetic algorithms; simulated annealing; supply chain management; uncertain systems; bilevel programming; crossover operation; evolutionary process; fuzzy demand; fuzzy simulation technology; genetic algorithm; integrated supply chain model; lower level programming; mutation operation; simulated annealing algorithm; uncertain programming; upper level programming; Costs; Educational institutions; Fuzzy systems; Genetic algorithms; Joining processes; Manufacturing; Raw materials; Simulated annealing; Supply chains; Uncertainty; Fuzzy simulation; Genetic algorithm; Integrated supply chain model; Simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems Conference, 2008 2nd Annual IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
978-1-4244-2149-7
Electronic_ISBN :
978-1-4244-2150-3
Type :
conf
DOI :
10.1109/SYSTEMS.2008.4519039
Filename :
4519039
Link To Document :
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