Intelligent Supply Chain Management

Mohammad Zubair Khan, Omar Al-Mushayt, Jahangir Alam, Jorair Ahmad

Faculty of Computer Science and Information System, University of Jizan, Jizan, Kingdom of Saudi Arabia.
University Women’s Polytechnic, Faculty of Engineering and Technology, Aligarh Muslim University, Aligarh, India..

DOI: 10.4236/jsea.2010.34045                

Abstract

Fuzzy Logic is used to derive the optimal inventory policies in the Supply Chain (SC) numbers. We examine the performance of the optimal inventory policies by cutting the costs and increasing the supply chain management efficiency. The proposed inventory policy uses multi-agent and Fuzzy logic, and provides managerial insights on the impact of the decision making in all the SC numbers. In particular, we focus on the way in which our agent purchases components using a mixed procurement strategy (combining long and short term planning) and how it sets its prices according to the prevailing market conditions and its own inventory level (because this adaptivity and flexibility are key to its success). In modern global market, one of the most important issues of the supply chain (SC) management is to satisfy changing customer demands and enterprises should enhance the long-term advantage through the optimal inventory control. In this paper an intelligent multi-agent system to simulate supply chain management has been developed.

Keywords

SCM Supply Chain Management, Customer Agent, RFQ, Component Agent

Conflicts of Interest

The authors declare no conflicts of interest.

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