A Talent Laboratory Resource Supply Chain Model Based on Fuzzy Analytic Technology

作者：Shih Sung Tsun^*; Chao Chian Yi; Hsu Chin Ming

来源：Life Science Journal-Acta Zhengzhou University Overseas Edition, 2012, 9(1): 56-63.

• Laboratory resource
• supply chain
• reasoning engine
• and fuzzy

This paper proposes a talent laboratory resource supply chain model for an educational institution to increase the integration, visibility and flexibility of the laboratory resource management. The proposed model utilizes a reasoning engine with fuzzy, parallel fuzzy rules, and de-fuzzy processes to decide the optimal purchase ordering quantity and the best constant stocks in the laboratory resource supply system. The fuzzy process takes the crisp input data through the characteristic function and maps the input data into its corresponding membership degree. The fuzzy rules are processed with different degree of membership and all rules in the system are processed before triggering an action. The de-fuzzy process takes each item's purchase ordering membership through the singleton output function and generates the corresponding crisp data. The proposed model allows users keying in their required experimental materials via the Web Site, uses the database management system to integrate all related information, and applies the fuzzy reasoning engine to generate the final purchase order reports to support the executor making the optimal decisions. [Sung-Tsun Shih, Chian-Yi Chao, Chin-Ming Hsu. A Talent Laboratory Resource Supply Chain Model Based on Fuzzy Analytic Technology. Life Science Journal. 2012; 9(1):56-63] (ISSN: 1097-8135). http://www.lifesciencesite.com.

• 出版日期2012