A multi-agent system model for company selection process in an ontology-based virtual enterprise

Virtual Enterprise (VE) is a collaboration model between multiple business partners in a value chain. VE information system deals with highly dynamic and continuously changing data and information from heterogeneous data sources. In order to manage and store dynamic VE information in the database, an ontology based VE model has been developed. To select which companies should exist with the VE, a Multi Agent System (MAS) has been developed. Communication and data transition among agents and system entities are based on defined rules in VE ontology model. One of the most important contributions of agents in VE system is in formation phase of VE. In partner selection stage of VE formation phase several agents with different goals and strategies are collaborating and competing with each other to win the negotiation procedure and also maximize the profit for their assigned enterprise. Different strategies are developed for the agents depending on their appetite for winning the auction against maximizing their profit. Several simulations were run and the results are stored. These results are fed into a neural network in order to predict which enterprise will win the auction and what will be the profit margin. The motivation is to provide a forecasting agent for the customers about the outcomes of the auctions so that they can plan ahead and take the necessary action. Early results indicate such simulated multi-agent VE formations can be used in real systems.