Fuzzy quantity discount optimization models of supply chain coordination based on credibility theory

Author

Wang, Junyan

Author_Institution

Dept. of Logistics Eng., Tianjin Univ. of Sci.& Technol., Tianjin

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

1210

Lastpage

1215

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICAL.2008.4636336

Filename

4636336