Multi Agent Systems Combined with Semantic Technologies for Automated Negotiation in Virtual Enterprises

In today’s competitive global markets, no company can be successful without effectively managing its supply chain. Procurement is a crucial process and it accounts for more than half of the enterprises’ sales volume. However, various problems have been identified in the past studies in this process: paper-based purchasing cycles and lack of automation, lack of intelligent advice tools for finding suitable suppliers, as well as difficulties to evaluate the performance of the suppliers (Lee et al. 2007). Appropriate supply chain organization will help companies to resolve conflicts, to reduce logistic lead times and total costs, to increase profits and to become more competitive on the market (Jain et al. 2009). Recent developments of electronic means for communication and collaboration between business partners led to the emergence of electronic negotiation as an alternative to manual contracting. The interest in e-negotiation is motivated by its potential to provide business partners with more efficient processes, enabling them to gain better contracts in less time (Rinderle and Benyoucef 2005). E-negotiation should allow automated or semi-automated processing of the information and transactions which take place between two companies and thus reduce costs and increase speed. However, by increasing the degree and the sophistication of the automation on both sides, commerce becomes much more dynamic, personalized, and context sensitive (He et al. 2003). A major challenge in distributed software development is the integration of knowledge scattered over processes, tools and people to facilitate an effective and efficient coordination of activities along the development lifecycle. The EU research FP7 focuses on a key strategic research challenge1 in the area of semantic systems/technology development to deal with the “growing load and diversity of information and content” which particularly applies to software engineering projects where semantic support for data analysis and reasoning would improve data and knowledge exchange among distributed project teams and promises more effective collaboration.