Fuzzy programming models of supplier selection based on network reputation

2013 ◽  
Vol 32 (6) ◽  
pp. 1749-1752
Author(s):  
Hua JIANG ◽  
Zhi-gang LU
Keyword(s):  
Supplier Selection ◽  
Fuzzy Programming ◽  
Programming Models

A Fuzzy Programming Model of Supplier Selection

2012 ◽  
Vol 468-471 ◽  
pp. 668-673 ◽  
Author(s):  
Hua Jiang ◽  
Zhi Gang Lu
Keyword(s):  
Supplier Selection ◽  
Programming Model ◽  
Fuzzy Programming ◽  
Chance Constrained Programming ◽  
Hybrid Intelligent Algorithm ◽  
Fuzzy Variables ◽  
Fuzzy Expected Value ◽  
Order Quantities ◽  
Constrained Programming ◽  
Fuzzy Programming Model

An integrated supplier selection problem under fuzzy environment is studied in this paper. Firstly, the linear weight method is used to calculate the scores of suppliers according to their different attributes, such as: quality, service, warranty, delivery, reputation and position, which are assumed as fuzzy variables. Secondly, a fuzzy expected value programming model and a fuzzy chance-constrained programming model are proposed to select the best combination of the suppliers and determine the order quantities. A hybrid intelligent algorithm, based on fuzzy simulation, genetic algorithm and neural network, is used to solve the two models. Finally, a numerical example is given to illustrate the effectiveness of the proposed models.

Supply Chain Coordination through a Revenue-Sharing Contract with Two Kinds of Fuzzy Demand

2014 ◽  
Vol 7 (4) ◽  
pp. 69-79 ◽  
Author(s):  
Junyan Wang ◽  
Xiazhong Li ◽  
Ziping Du
Keyword(s):  
Supply Chain ◽  
Supply Chain Coordination ◽  
Fuzzy Programming ◽  
Revenue Sharing ◽  
Programming Models ◽  
Elastic Demand ◽  
Demand Model ◽  
Fuzzy Environment ◽  
Revenue Sharing Contract ◽  
Linear Demand

This paper studies a supply chain coordinated by a revenue-sharing contract in fuzzy environment. Two kinds of fuzzy programming models are discussed: revenue-sharing contract with fuzzy linear demand model and fuzzy iso-price-elastic demand model. Supply chain coordination in both centralized decision setting and centralized decision setting are achieved by obtaining the optimal solutions in the discussed settings.

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