A Multi-agent System Model for Partner Selection Process in Virtual Enterprise
| Autor: | Ahmet Murat Ozbayoglu, F. Arikan, Sadik Engin Kilic, B. Lotfi Sadigh, Hakki Ozgur Unver |
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| Přispěvatelé: | TOBB ETU, Faculty of Engineering, Department of Computer Engineering, TOBB ETU, Faculty of Engineering, Department of Mechanical Engineering, TOBB ETÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, TOBB ETÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümü, Özbayoğlu, Ahmet Murat, Ünver, Hakkı Özgür, H-2328-2011 |
| Rok vydání: | 2014 |
| Předmět: |
learning agents
Knowledge management Process management business.industry Computer science Multi-agent system media_common.quotation_subject Multi-agent systems virtual enterprise Profit (economics) Negotiation Ontology Profit margin Information system General Earth and Planetary Sciences Common value auction ontology business General Environmental Science media_common |
| Zdroj: | Complex Adaptive Systems |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2014.09.007 |
| Popis: | Conference on Conquering Complexity - Challenges and Opportunities (2014 : Philadelphia, PA) 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. SAN-TEZ of Turkish Ministry of Science, Technology and Industry [00979.stz.2011-12] |
| Databáze: | OpenAIRE |
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