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Decision Function Implementation in MAREA Simulations Influencing Financial Balance of Small-Sized Enterprise

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Agent and Multi-Agent Systems: Technology and Applications (KES-AMSTA 2017)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 74))

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Abstract

The aim of this paper is to present the use of a decision function in the implementation of a multi-agent simulation model of a small-sized enterprise dealing with trading. The subject of the presented research are simulation experiments in MAREA software framework, which was designed to simulate trading behaviour of a trading company. Firstly, we present a multi-agent system and a mathematical description of a decision function, which is used to establish the price of traded goods. Secondly, we present MAREA software framework and lastly we discuss the simulation results of company dealing with retailing of fluorescence colours. The results obtained show that simulation experiments in MAREA could be used to support the decision-making process of a management of trading companies in the scope of predicting key performance indicators and changes of parameters and their impact on the company’s financial balance.

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References

  1. Suchanek, P., Vymetal, D.: Security and disturbances in e-commerce systems. In: Proceedings of the 10th International Conference Liberec Economic Forum 2011 (2011). ISBN: 978-80-7372-755-0

    Google Scholar 

  2. Gries, M., Kulkarni, Ch., Sauer, Ch., Keutzer, K.: Comparing Analytical Modeling with Simulation for Network Processors: A Case Study. University of California, Berkeley; Infineon Technologies, Corporate Research, Munich (2011). https://pdfs.semanticscholar.org/83a4/bc3623b74c360512224cb8227bb1dbfd3d51.pdf. Accessed 13 Sep 2016

  3. Liu, Y., Trivedi, K.S.: Survivability Quantification: The Analytical Modeling Approach. Department of Electrical and Computer Engineering. Duke University, USA, Durham. http://people.ee.duke.edu/~kst/surv/IoJP.pdf. Accessed 21 Jan 2016

  4. Macal, C.M., North, M.J.: Tutorial on agent-based modeling and simulation. In: Proceedings of the Winter Simulation Conference, pp. 2–15 (2005)

    Google Scholar 

  5. Scheer, A.-W., Nüttgens, M.: ARIS architecture and reference models for business process management. In: van der Aalst, W., Desel, J., Oberweis, A. (eds.) Business Process Management. LNCS, vol. 1806, pp. 376–389. Springer, Heidelberg (2000). doi:10.1007/3-540-45594-9_24

    Chapter  Google Scholar 

  6. Sierhuis, M.: Modeling and simulating work practice. Ph.D. thesis, University of Amsterdam (2001)

    Google Scholar 

  7. Barnett, M.: Modeling & Simulation in Business Process Management. Gensym Corporation, pp. 6–7 (2003). http://w.businessprocesstrends.com/publicationfiles/11-03%20WP%20Mod%20Simulation%20of%20BPM%20-%20Barnett-1.pdf. Accessed 21 Jan 2016

  8. Vymetal, D., Sperka, R.: Virtual company simulation for distance learning. In: Proceedings of the Distance Learning Simulation and Communication Conference, Brno, Czech Republic (2013). ISBN: 978-80-7231-919-0

    Google Scholar 

  9. Sharma, S., Sharma, J., Devi, A.: Corporate social responsibility: the key role of human resource management. Bus. Intell. J. 2, 205–213 (2009). http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.514.7758&rep=rep1&type=pdf. Accessed 13 Sep 2016

    Google Scholar 

  10. Vymetal, D., Sperka, R.: MAREA - from an agent simulation application to the social network analysis. Procedia Comput. Sci. 35, 1416–1425 (2014). doi:10.1016/j.procs.2014.08.198. Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems 18th Annual Conference – KES 2014, Gdynia, Poland

    Article  Google Scholar 

  11. Vymětal, D., Spišák, M., Šperka, R.: An influence of random number generation function to multiagent systems. In: Jezic, G., Kusek, M., Nguyen, N.-T., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2012. LNCS(LNAI), vol. 7327, pp. 340–349. Springer, Heidelberg (2012). doi:10.1007/978-3-642-30947-2_38

    Chapter  Google Scholar 

  12. Spisak, M., Sperka, R.: Financial market simulation based on intelligent agents - case study. J. Appl. Econ. Sci. VI 3(17), 249–256 (2011). http://www.jaes.reprograph.ro/articles/winter2011/JAES_Fall_2011_online.pdf. Accessed 13 Sep 2016. Romania, Print ISSN: 1843-6110

    Google Scholar 

  13. Šperka, R., Spišák, M.: Transaction costs influence on the stability of financial market: agent-based simulation. J. Bus. Econ. Manag. 14(Suppl. 1), S1–S12 (2013). doi:10.3846/16111699.2012.701227. Taylor & Francis, United Kingdom, London. Print ISSN: 1611-1699

    Google Scholar 

  14. Šperka, R., Vymětal, D.: MAREA - an education application for trading company simulation based on REA principles. In: Proceedings of the Information, Communication and Education Application, ICEA 2013. Advances in Education Research, vol. 30, Hong Kong, China, 1–2 November 2013, pp. 140–147. Information Engineering Research Institute (IERI), Delaware (2013). ISBN: 978-1-61275-056-9

    Google Scholar 

  15. Foundation for Intelligent Physical Agents, FIPA: FIPA Contract Net Interaction Protocol. In Specification (2002). http://www.fipa.org/specs/fipa00029/SC00029H.html. Accessed 21 Jan 2016

  16. Vymětal, D., Scheller, C.: MAREA: multi-agent REA-Based business process simulation framework. In: Proceedings of the International Scientific Conference ICT for Competitiveness, pp. 301–310. OPF SU, Karviná (2012). ISBN: 978-80-7248-731-8

    Google Scholar 

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Acknowledgement

The work was supported by SGS/19/2016 project of Silesian University in Opava, Czech Republic, Europe called “Advanced mining methods and simulation techniques in business process domain”.

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Correspondence to Roman Šperka .

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Šperka, R., Musil, D. (2018). Decision Function Implementation in MAREA Simulations Influencing Financial Balance of Small-Sized Enterprise. In: Jezic, G., Kusek, M., Chen-Burger, YH., Howlett, R., Jain, L. (eds) Agent and Multi-Agent Systems: Technology and Applications. KES-AMSTA 2017. Smart Innovation, Systems and Technologies, vol 74. Springer, Cham. https://doi.org/10.1007/978-3-319-59394-4_13

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  • DOI: https://doi.org/10.1007/978-3-319-59394-4_13

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