Research On Manufacturing Scheduling And Conflict Resolution In Virtual Enterprises Based On Multi-Agent Cooperation

With the developing of information technology and uniting of global economy, modern enterprises are facing with new challenges. The Virtual Enterprise (VE) becomes the idea organization modal adapting to the market and realizing the cooperation and competition at the same time.Multi-Agent Systems (MAS) is a hot topic of Distributed Artificial Intelligence (DAI). Researches on MAS focus on agents how to coordinate their knowledge, goals, strategies and plans to act or solve problems cooperatively. Theories of MAS are fit for solving interaction problems in distributed, dynamic and open systems. Its problem domain coincides with that of scheduling and conflict resolution in virtual enterprise.According to the properties of virtual enterprises, its system architecture is presented and ameliorated strategies of multi-agent cooperation and intelligent optimization algorithms are used to deal with task scheduling and conflict resolution in virtual enterprises. An information infrastructure of multi-agent system is built to support the operation of virtual enterprises.This paper is written along the line of problem-theory-application. The main contributions of the paper consist of:(1)A tri-dimension virtual enterprise system architecture is presented with life cycle of VE, views modeling and system plats. In the fashion ofsupply chain management and modeling with business process, the virtual enterprises can be organized and operated in collaborative commerce information environment.(2)A learning negotiation model with Bayesian Decision Making is set up which improves the contract net protocol (CNP) and makes it possible that the cooperative problems in virtual enterprises can be solved with cooperation theories of MAS. The multi-attribution utility theory (MAUT) is adopted to analyze the decision support during negotiation process with AHP method and trigonometric fuzzy function, which supplies the integrated resolution scheme to MAS negotiation.(3)A distributed, autonomic and collateral task scheduling model is built, in which the task decomposed with agent ability matching and scheduled with Partial-Global-Plan (PGPG) strategy. The Bayesian negotiation and MAUT are also used in task scheduling and re-scheduling with an integrated optimization algorithms base, which makes the scheduling system adapt to uncertain, dynamic, complex market environment.(4)Combining the conflict avoiding with conflict resolution, an integrated conflict strategy ensures that the virtual enterprises run coordinately. The fuzzy reasoning used to choose the strategy intelligently expedites the conflict resolution process and makes the VE response to the market faster.(5)The agent modeling technology is adopted to build VE model and domain knowledge is described by ontology. After analyzing agent communication, a mutually operation and plat independent soft resolution scheme is put forward for VE system. The information infrastructure of multi-agent system is built to realize the collaborative production management system of VE, which develops the Agent Oriented Programming (AOP) method.