Title :
Supply and Demand Matching Model for Third Party Logistics Integrated Platform
Author :
Ju, Chunhua ; Sun, Bin
Author_Institution :
Comput. Sci. & Inf. Eng. Coll., Zhejiang Gongshang Univ., Hangzhou, China
Abstract :
In order to improve the supplier selection and matching supply with demand for third party logistics integrated platform, this paper proposes a three-layer evaluation index system for supply and demand matching considering factors of service areas and cooperation experiences, establishes a supply and demand matching model based on neural network. This model perfectly simulates the process of fuzzy integral diagnosis, with corresponding parameters of adaptive learning and training index systems of fuzzy neural network. Experiments show that this model can effectively evaluate comprehensive abilities of suppliers, with high level of accuracy and feasibility.
Keywords :
fuzzy neural nets; industrial economics; learning (artificial intelligence); logistics; supply and demand; supply chain management; adaptive learning; fuzzy integral diagnosis process; fuzzy neural network training; supplier selection; supply chain management; supply-and-demand matching model; third party logistics integrated platform; three-layer evaluation index system; Computer science; Educational institutions; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Logistics; Neural networks; Neurons; Supply and demand; Supply chains; fuzzy neural network; integrated model; supply and demand matching; third party logistics;
Conference_Titel :
Artificial Intelligence, 2009. JCAI '09. International Joint Conference on
Conference_Location :
Hainan Island
Print_ISBN :
978-0-7695-3615-6
DOI :
10.1109/JCAI.2009.160