Actual status of management confirms usefulness and necessity for development of scientific modeling tools for decision-making processes based on distributed artificial intelligence. The paper presents opportunities of the agent – oriented approach to support operative and strategic management decisions at the pharmaceutical enterprise. It is argued that the combination of intelligent agents technology and Data Mining (DM) produces a powerful synergistic effect. The basis of the intellectual agent – oriented DSS (AODSS) is proposed to put a hybrid approach to the use of DM. Hybrid intelligent AODSS is represented numerous network of small agents, it provides concurrent operation execution, solutions distribution, knowledge management. Agents can be divided into groups: data agents, monitoring agents, agents for solutions search, modeling agents, impact agents and presentations agents. The result of research is development of AODSS created as a multi-level system wherein the project, process and environment levels are intercommunicated. The combination of intelligent technologies in AODSS allows involve rules, cases, a wide range of DM methods and models. The paper proposes a variant of AODSS implementation within the real enterprise IT-infrastructure based on SAP NetWeaver. The analysis results of the semi-commercial operation of the system assures that it can improve managerial decisions inasmuch as accuracy, consistency, flexibility, speed together form the basis of actual efficient solutions.
Keywords: agent-oriented system, decision support, data mining, hybrid approach, model.
DOI: http://dx.doi.org/10.17721/1728-2667.2014/160-7/20
References
- Wooldridge, M. and Jennings, N., 1995. Intelligent Agents: Theory and Practice. [pdf] Available at: [Accessed 15 March 2014].
- Ivashkin, Ju.A., 2013. Agent technologies and multiagent systems modeling. Moscow: MFTI. (Russian)
- Yershov, S.V., 2013. The theoretical basis of the model-based construction of fuzzy intelligent multiagent systems. Ph.D. Nat. Acad. Sciences of Ukraine, Institute of Cybernetics Glushkov (Ukrainian)
- Castillo O., Melin P., Pedrycz W. and Kacprzyk J. eds., 2014. Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Berlin: Springer.
- Medsker, L.R., 2013. Hybrid Intelligent Systems. Boston: Springer.
- Siddique, N., 2014. Intelligent Control: A Hybrid Approach Based on Fuzzy Logic, Neural Networks and Genetic Algorithms. Berlin: Springer.
- Railsback, S.F. and Grimm V., 2011. Agent-Based and Individual-Based Modeling: A Practical Introduction. Princeton University Press.
- Subbotin, S.O. ed., 2009. Non-iterative, evolutionary and multiagent methods for the synthesis of fuzzy logic and neural network models. Zaporizhzhia: ZNTU. (Ukrainian)
- Shvecov, A.N., 2012. Agent-oriented systems: the basic models. Vologda: VoGTU. (Russian).
- Ventre, A.G., Maturo A., Hosková-Mayerová S. and Kacprzyk J., 2013. Multicriteria and Multiagent Decision Making with Applications to Economics and Social Sciences. Springer.
- Huzhva, V.M., 2002. Modeling of multiagent systems for logistics management in enterprises. Ph.D. Kyiv National Economic University. (Ukrainian)
- Rogozin, O.V., 2012. Methods and models for support of innovative solutions in the agent-oriented systems. Moscow: MJeSI. (Russian)
- Romanov, V.P. and Lel’chuk A.V., 2013. Multiagent Systems in Economics. Moscow: RJeU im. G.V. Plehanova. (Russian)
- Skobelev, P.O. Multi-agent technology for enterprise resource management in real time [online] Available at: [Accessed 17 March 2014]. (Russian)
- Srinivasan D. ed., 2013. Innovations in Multi-Agent Systems and Application. Springer.
- Trajkovski G., 2010. Developments in Intelligent Agent Technologies and Multi-Agent Systems: Concepts and Applications. IGI Global.
- Tjurin, I.Ju., Vylegzhanin, A.S., Andreev, M.V., Kol’bova, Je.V., Skobelev, P.O. and Shepilov Ja.Ju. Implementation results and prospects of multi-agent system for operational management tool shop of JSC “Izhevsk Motor – Axion Holding” [online] Available at: [Accessed 7 March 2014] (Russian)
- Rzhevskij D. Multi-agent systems in logistics and e-commerce [online] Available at: [Accessed 10 March 2014] (Russian)
- Tarasov, V.B., 2002. From multiagent systems to intelligent organizations: philosophy, psychology, computer science. Moscow: URSS. (Russian)
- Chornous, G.O., 2012. Proactive decision-making mechanizm based on mining technology. Ekonomica (Economics), 91(1), рр.105–118.
- Chornous, G.O., 2013. Hybrid use of methods of intellectual analyses of data for modeling processes of proactive management. Bussiness Inform, 4, pp.172–177. (Ukrainian)
- Chornous, G.O., 2012. Modeling of socio-economic systems patterns based on balanced strategic measurement methods. Bulletin of Taras Shevchenko National University of Kyiv. Economics, 135, pp. 61–63. (Ukrainian)
- Hilgefort, I., 2011. Reporting and Analysis with SAP BusinessObjects. SAP PRESS.