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Simulation of Supply Chain with Disturbances Using Flexsim - Case Study

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Book cover Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability - The PAAMS Collection (PAAMS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 524))

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Abstract

The aim of the paper is to present a simulation model of transportation which includes different disturbances. The paper describes in detail modeled route and way of modeling some disturbances. In article authors presented influence of distinguished distortion to time of realization transport task. Authors create own object with using Discrete Event Simulation and Agent Based Simulation approach. The research highlights of the performed works are as follows: showing influence of disturbances to transportation time and present a description to build objects, which represent disturbances.

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References

  1. Alteren, B., Hokstad, P., Moe, D., Sakshaug, K.: A barrier model for road traffic applied to accident analysis. In: Spitzer, C., et al. (eds.) Probabilistic Safety Assessment and Management, pp. 3603–3608. Springer, London (2004)

    Chapter  Google Scholar 

  2. Bae, J.W., Lee, G., Moon, I.: Introductory tutorial: agent-based modeling and simulation. In: Winter Simulation Conference, pp. 3809–3820 (2012)

    Google Scholar 

  3. Banks, J., Carson II, J.S., Nelson, B.L., Nicol, D.M.: Discrete-Event System Simulation, 4th edn, pp. 68–86. Prentice Hall, Upper Saddle River (2004). ISBN 0-13-144679-7

    Google Scholar 

  4. Bocewicz, G.: Robustness of multimodal transportation networks. Eksploatacja i Niezawodność-Maintenance and Reliability 16(2), 259–269 (2014)

    Google Scholar 

  5. Brussaard, L.A., Kruiskamp, M.M., Oude Essink, M.P.: The Dutch Model for the quantitative risk analysis of road tunnels. In: Spitzer, C., et al. (eds.) Probabilistic Safety Assessment and Management, pp. 2660–2665. Springer, London (2004)

    Chapter  Google Scholar 

  6. Caddy, I.N., Helou, M.M.: Supply chains and their management: application of general systems theory. J. Retail. Consum. Serv. 14, 319–327 (2007)

    Article  Google Scholar 

  7. Cassandras, C.G., Lafortune, S.: Introduction to Discrete Event Systems, 2nd edn, pp. 557–615. Springer, Heidelberg (2008). ISBN 978-0-387-33332-8

    Book  MATH  Google Scholar 

  8. Chan, W.K.V., Son, Y., Macal, C.M.: Agent-based simulation tutorial – simulation of emergent behavior and differences between Agent-Based Simulation and Discrete-Event Simulation. In: Winter Simulation Conference, pp. 135–150 (2010)

    Google Scholar 

  9. Chen, S., Peng, H., Liu, S.: Yang, Y.: A Multimodal Hierarchical-based Assignment Model for Integrated Transportation Networks. J. Transp. Syst. Eng. Inf. Technol. 9(6), 130–135 (2009)

    Google Scholar 

  10. Fung, R.Y.K., Chen, T.: A multiagent supply chain planning and coordination architecture. Int. J. Adv. Manuf. Technol. 25(7–8), 811–819 (2004)

    Google Scholar 

  11. Gheorghe, A., Birchmeier, J., Kröger, W.: Advanced spatial modelling for risk analysis of transportation dangerous goods. In: Spitzer, C., et al. (eds.) Probabilistic Safety Assessment and Management, pp. 2499–2504. Springer, London (2004)

    Chapter  Google Scholar 

  12. Hoffa, P., Pawlewski, P.: Agent based approach for modeling disturbances in supply chain. In: Corchado, J.M., et al. (eds.) Highlights of Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection, pp. 144–155. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  13. Jasiulewicz-Kaczmarek, M.: Role and contribution of maintenance in sustainable manufacturing. In: Bakhtadze N., Chernyshov K., Dolgui A., Lototsky V., (eds.) 7th IFAC Conference on Manufacturing Modelling, Management, and Control, part 1, vol. 7, pp. 1146–1151 (2013)

    Google Scholar 

  14. Kim, S.-H., Robertazzi, T.G.: Modeling Mobile Agent Behavior. Comput. Math. Appl. 51, 951–966 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  15. Macal, C.M., North, M.J.: Introductory tutorial: agent-based modeling and simulation. In: Winter Simulation Conference, pp. 362–376 (2013)

    Google Scholar 

  16. Marseguerra, M., Zio, E., Bianchi, M.: A fuzzy model for the estimate of the accident rate in road transport of hazardous materials. In: Bedford, T., van Gelder, P.H.A.J.M. (eds.) Safety and Reliability, pp. 1085–1092. Swets & Zeitlinger, Lisse (2003)

    Google Scholar 

  17. Orlandelli, C.M., Vestrucci, P.: Development of a road transportation risks data base for Italy: methodology, models and results. In: Spitzer, C., et al. (eds.) Probabilistic Safety Assessment and Management, pp. 2269–2274. Springer, London (2004)

    Chapter  Google Scholar 

  18. Siebers, P.O., Macal, C.M., Garnett, J., Buxton, D., Pidd, M.: Discrete-event simulation is dead, long live agent-based simulation! J. Simul. 4(3), 204–210 (2010)

    Article  Google Scholar 

  19. Sitek P., Wikarek J.: A hybrid approach to supply chain modeling and optimization. In: Federated Conference on Computer Science and Information Systems, pp. 1223–1230 (2013)

    Google Scholar 

  20. Skorupski, J.: Sieci Petriego jako narzędzie do modelowania procesów ruchowych w transporcie, Prace Naukowe Politechniki Warszawskiej, Transport, z.78, pp.69–84 (2011)

    Google Scholar 

  21. Tixier, J., et al.: Development of a risk knowledge platform dedicated to accident of dangerous goods transportation. In: Guedes Soares, G., Zio, E. (eds.) Safety and Reliability for Managing Risk, pp. 117–122. Taylor & Francis Group, London (2006)

    Google Scholar 

  22. Umeda, S.: Simulation analysis of supply chain systems with reverse logistics. In: Winter Simulation Conference, pp. 3375–3384 (2013)

    Google Scholar 

  23. Wieland, A., Wallenburg, C.M.: Supply-Chain-Management in stürmischen Zeiten, Berlin. (2011)

    Google Scholar 

  24. Wilhelm, T., Hollunder, J.: Information theoretic description of networks. Phys. A 385(1), 385–396 (2007)

    Article  MathSciNet  Google Scholar 

  25. http://autostrada-a2.pl. Accessed Jan 2015

  26. https://www.flexsim.com/. Accessed Jan 2015

  27. http://www.gddkia.gov.pl. Accessed Jan 2015

  28. http://gddkia.gov.pl/pl/aprint/6636/mapa-i-spis-czarnych-punktow. Accessed Jan 2015

  29. http://isap.sejm.gov.pl/. Accessed Jan 2015

  30. https://mapa.targeo.pl. Accessed Jan 2015

  31. http://www.rmf24.pl/fakty/polska/news-szokujacy-raport-o-polskich-drogach-zobacz-mape-czarnych-odc,nId,769924. Accessed Jan 2015

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Acknowledgements

Presented research are carried out under the LOGOS project (Model of coordination of virtual supply chains meeting the requirements of corporate social responsibility) under grant agreement number PBS1/B9/17/2013.

Author information

Authors and Affiliations

  1. Poznan University of Technology, ul.Strzelecka 11, 60-965, Poznań, Poland

    Patycja Hoffa & Pawel Pawlewski

Authors
  1. Patycja Hoffa
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  2. Pawel Pawlewski
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Corresponding author

Correspondence to Patycja Hoffa .

Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain

    Javier Bajo

  2. University of Southern Denmark, Odense, Denmark

    Kasper Hallenborg

  3. Faculty of Engineering Management, Poznan University, Poznan, Poland

    Pawel Pawlewski

  4. Departamento de Sistemas Informáticos y Computación, Polytechnic University of Valencia, Valencia, Spain

    Vicente Botti

  5. Fluminense Federal University, Rio de Janeiro, Brazil

    Nayat Sánchez-Pi

  6. Universidad Nacional de Colombia, Manizales, CALDAS, Colombia

    Nestor Darío Duque Méndez

  7. Lab. Nacional de Energia e Geologia, Lisbon, Portugal

    Fernando Lopes

  8. Universidad Politécnica de Valencia, Valencia, Spain

    Vicente Julian

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Hoffa, P., Pawlewski, P. (2015). Simulation of Supply Chain with Disturbances Using Flexsim - Case Study. In: Bajo, J., et al. Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability - The PAAMS Collection. PAAMS 2015. Communications in Computer and Information Science, vol 524. Springer, Cham. https://doi.org/10.1007/978-3-319-19033-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-19033-4_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19032-7

  • Online ISBN: 978-3-319-19033-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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