Designing A Multi-Agent System For Improving Supply Chain Performance

Autor: Darya Plinere, Yuri Merkurvev
Rok vydání: 2019
Předmět:
Zdroj: 2019 IEEE 7th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE).
Popis: Nowadays, the dynamically changing environment requires a timely response to changes in the supply chain. The authors focus on a multi-agent system as an approach to improving supply chain performance. Software agents are successfully applied in supply chain management tasks. Agent behaviour is defined according to the purpose of its development. Multi-agent systems can be used for domain areas that include negotiations between different firms or people with different goals and confidential information available. Supply chain can be represented by an intelligent agent set, where each agent is responsible for one or more functions of the supply chain. Existing multi-agent systems have shown successful results, but these systems have always been developed for each case individually, there is no any universal multi-agent system. The paper discusses the development of a new multi-agent system for supply chain management. The paper provides a sequence of actions for the system development starting from discussing supply chain processes and tasks that represent behaviour of agents. The authors also propose to develop a multi-agent system that can improve supply chain performance and present performance measurement for the system. The proposed multi-agent system provides demand forecasting, inventory management and production scheduling aimed at improving the supply chain performance.
Databáze: OpenAIRE