Title :
Fuzzy quantity discount optimization models of supply chain coordination based on credibility theory
Author_Institution :
Dept. of Logistics Eng., Tianjin Univ. of Sci.& Technol., Tianjin
Abstract :
This paper characterizes market demand and production cost as fuzzy variables due to their uncertainty based on credibility theory. And proposes two kinds quantity discount optimization models of supply chain coordination: fuzzy expected value quantity discount programming model and fuzzy chance-constraint quantity discount programming model. In the end, a genetic algorithm based on fuzzy simulation is designed to solve the proposed models.
Keywords :
fuzzy set theory; genetic algorithms; supply chain management; credibility theory; fuzzy chance-constraint quantity discount programming model; fuzzy expected value quantity discount programming model; fuzzy quantity discount optimization model; fuzzy simulation; fuzzy variables; genetic algorithm; market demand; production cost; supply chain coordination; Algorithm design and analysis; Automation; Cost function; Fuzzy set theory; Genetic algorithms; Logistics; Optimized production technology; Probability distribution; Supply chains; Uncertainty; Fuzzy Variable; Optimization Model; Quantity Discount; Supply Chain Coordination;
Conference_Titel :
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-2502-0
Electronic_ISBN :
978-1-4244-2503-7
DOI :
10.1109/ICAL.2008.4636336
