Research Of The Optimization Strategy And Its Application Of Supply Chain Processes Based On HTN

The supply chain management involves a potentially large number of business processes performed by a number of different parties. The supply chain could be operated efficiently only when these activities or relations was identified and managed. The CIMS applied widely in traditional industry systems cannot meet the demands of the agility manufacturing for it usually has centered architecture and depends on the global planning so as to be a inflexible alternative.This dissertation views the optimization from standpoint of supply chain tasks on product and services. Firstly, on the basis of feature analysis of supply chain, the planning technologies, which are widely used in distributed intelligent artificial domain, could be applied to the optimization of supply chain through the policy of task representation and decomposition. Furthermore, on the practical level a multi-agent system combined with the hierarchical task network (HTN) was established to handle the complexity of supply chain management. The system was based on the identification and models of the key activities of the parts of the supply chain and on the intelligent tasks decomposition and dispatch based on the communication among software agents. Finally, this paper gives the steps and schema to optimize the supply chain based on HTN, and takes the practical supply chain processes as research object according to the efforts of UN/CAEFECT (United Nations Center for Trade Facilitation and Electronic Commerce) and adopted the ebXML architecture.Aimed at planning and scheduling the business processes efficiently, the optimization strategy of supply chain process operation is developed. To archive complex supply chain processes management, the integration of business and information among the enterprises is enforced on basis of decomposition and dispatch of the production or service tasks, the cooperation between the entities of the supply chain, as well the sufficiency application of the production resource.