A Multi-Agent System Model for Partner Selection Process in Virtual Enterprise

No Thumbnail Available

Date

2014

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier Science Bv

Research Projects

Organizational Units

Organizational Unit
Department of Mechanical Engineering
(2016)
The Mechanical Engineering Doctoral Program has started in 2016-2017 academic year. We have highly qualified teaching and research faculty members and strong research infrastructure in the department for graduate work. Research areas include computational and experimental research in fluid and solid mechanics, heat and mass transfer, advanced manufacturing, composites and other advanced materials. Our fundamental mission is to train engineers who are able to work with advanced technology, create innovative approaches and authentic designs, apply research methods effectively, conduct research and develop high quality methods and products in space, aviation, defense, medical and automotive industries, with a contemporary education and research infrastructure.

Journal Issue

Abstract

Virtual Enterprise (VE) is a collaboration model between multiple business partners in a value chain. VE information system deals with highly dynamic 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 winner enterprises in 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 partner selection step of VE formation phase. In this step several agents with different goals and strategies are collaborating and competing each other to win the negotiation procedure or maximize the profit for their assigned enterprise. Different strategies are developed for the agents depending on their appetite for winning the auction against maximizing the 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. A Multi-Agent System Model for Partner Selection Process in Virtual Enterprise (C) 2014 Published by Elsevier B.V.

Description

Sadigh, Bahram Lotfi/0000-0002-3027-3734; Ozbayoglu, Ahmet/0000-0001-7998-5735; UNVER, HAKKI OZGUR/0000-0002-4632-3505

Keywords

Multi-agent systems, virtual enterprise, ontology, learning agents

Turkish CoHE Thesis Center URL

Citation

10

WoS Q

Scopus Q

Source

Conference on Conquering Complexity - Challenges and Opportunities -- NOV 03-05, 2014 -- Philadelphia, PA

Volume

36

Issue

Start Page

367

End Page

+

Collections