Agent-Based Simulation in Logistics and Supply Chain Research: Literature Review and Analysis

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Advances in Production, Logistics and Traffic (ICPLT 2019)

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Abstract

In complex supply chains decision-makers strive to act quickly and effectively to ensure the efficient operation of their systems. Particularly, at the operational level immediate decision-making is required. In this context, simulation is becoming increasingly important for decision-making in logistics and supply chain. The classic event-discrete simulation paradigm is reaching its limits in the modelling of individual interacting system components of complex socio-technical systems due to a lack of flexibility and adaptability. The agent-based simulation (ABS) paradigm offers the capability to design heterogeneous individuals as agents that interact with each other as well as with the environment. This paper analyses the state-of-the-art of ABS in literature with a focus on operational logistics. We use a multi-level classification framework to provide a literature overview for publications of the operational logistics research field from in the recent years. On the basis of the literature review, categories are identified which may indicate research gaps.

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References

  • Abar, S., Theodoropoulos, G.K., Lemarinier, P., O’Hare, G.M.P.: Agent based modelling and simulation tools a review of the state-of-art software. Comput. Sci. Rev. 24, 13–33 (2017)

    Article  Google Scholar 

  • Ait-Kadi, D., Chouinard, M., Marcotte, S., Riopel, D.: Sustainable Reverse Logistics Network Engineering and Management. ISTE, Wiley, London, Hoboken (2012)

    Book  Google Scholar 

  • Amini, M., Wakolbinger, T., Racer, M., Nejad, M.G.: Alternative supply chain production–sales policies for new product diffusion an agent-based modeling and simulation approach. Eur. J. Oper. Res. 216(2), 301–311 (2012)

    Article  Google Scholar 

  • Behdani, B.: Evaluation of paradigms for modeling supply chains as complex socio-technical systems. In: Proceedings of the 2012 Winter Simulation Conference (WSC). IEEE, Piscataway, New Jersey (2012)

    Google Scholar 

  • Besenfelder, C., Brüggenolte, M., Austerjost, M., Kämmerling, N., Pöting, M., Schwede, D.-I.C., Schellert, M.: Paradigmenwechsel der Planung und Steuerung von Wertschöpfungsnetzen. Unter Mitarbeit von Michael ten Hompel, Michael Henke und Uwe Clausen (2017)

    Google Scholar 

  • Chan, H.K., Chan, F.T.S.: Comparative study of adaptability and flexibility in distributed manufacturing supply chains. Decis. Support Syst. 48(2), 331–341 (2010)

    Article  MathSciNet  Google Scholar 

  • Chen, X., Ong, Y.-S., Tan, P.-S., Zhang, N., Li, Z.: Agent-based modeling and simulation for supply chain risk management - a survey of the state-of-the-art. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics, pp. 1294–1299. IEEE (2013)

    Google Scholar 

  • Chopra, S., Meindl, P.: Supply Chain Management Strategy, Planning, and Operation, 6th Global edn. Pearson, Boston (2016)

    Google Scholar 

  • Clausen, U., Brueggenolte, M., Kirberg, M., Besenfelder, C., Poeting, M., Güller, M.: List of Categorized Publications (2018). https://1drv.ms/f/s!AiEgswzazr3VfLZXuOtkHXHHJ70. Accessed 30 Oct 2018

  • Davidsson, P., Henesey, L., Ramstedt, L., Törnquist, J., Wernstedt, F.: An analysis of agent-based approaches to transport logistics. Transp. Res. Part C Emerg. Technol. 13(4), 255–271 (2005)

    Article  MATH  Google Scholar 

  • Femerling, J.C., Gleißner, H.: Logistics Basics - Exercises - Case Studies. Springer, Cham (2013). (Springer Texts in Business and Economics)

    Google Scholar 

  • Fikar, C., Hirsch, P., Nolz, P.C.: Agent-based simulation optimization for dynamic disaster relief distribution. Cent. Eur. J. Oper. Res. 12(4), 301 (2017)

    Google Scholar 

  • Garro, A., Monaco, M.F., Russo, W., Sammarra, M., Sorrentino, G.: Agent-based simulation for the evaluation of a new dispatching model for the straddle carrier pooling problem. Simulation 91(2), 181–202 (2015)

    Article  Google Scholar 

  • Gath, M., Wagner, T., Herzog, O.: Autonomous logistics processes of bike courier services using multiagent-based simulation. In: The 11th International Conference on Modeling and Applied Simulation, pp. 134–142. DIME, Univ. di Genova, Genova (2012)

    Google Scholar 

  • Heath, B.L., Hill, R.R.: Some insights into the emergence of agent-based modelling. J. Simul. 4(3), 163–169 (2010)

    Article  Google Scholar 

  • Hongler, M.-O., Gallay, O., Hülsmann, M., Cordes, P., Colmorn, R.: Centralized versus decentralized control—a solvable stylized model in transportation. Phys. A Stat. Mech. Its Appl. 389(19), 4162–4171 (2010)

    Article  Google Scholar 

  • Klügl, F., Bazzan, A.L.C.: Agent-based modeling and simulation. AIMag 33(3), 29 (2012)

    Article  Google Scholar 

  • Krejci, C.C.: Hybrid simulation modeling for humanitarian relief chain coordination. J. Hum. Logist. Supply Chain. Manag. 5(3), 325–347 (2015)

    Article  MathSciNet  Google Scholar 

  • Law, A.M.: Simulation Modeling and Analysis, 5th edn. McGraw-Hill, New York (2015)

    Google Scholar 

  • Lima, A.D.P., Werner de Mascarenhas, F., Frazzon, E.M.: Simulation-based planning and control of transport flows in port logistic systems. Math. Probl. Eng. 2015(1), 1–12 (2015)

    Article  Google Scholar 

  • Macal, C.M.: Everything you need to know about agent-based modelling and simulation. J. Simul. 10(2), 144–156 (2016)

    Article  Google Scholar 

  • Macal, C.M., North, M.J.: Tutorial on agent-based modelling and simulation. J. Simul. 4(3), 151–162 (2010)

    Article  Google Scholar 

  • Van Dyke Parunak, H.: Agents in overalls experiences and issues in the development and deployment of industrial agent-based systems. Int. J. Coop. Inf. Syst. 09(03), 209–227 (2000)

    Article  Google Scholar 

  • Pegden, C.D.: Advanced tutorial: overview of simulation world views. In: Proceedings of the 2010 Winter Simulation Conference, pp. 210–215 (2010)

    Google Scholar 

  • Sarraj, R., Ballot, E., Pan, S., Hakimi, D., Montreuil, B.: Interconnected logistic networks and protocols simulation-based efficiency assessment. Int. J. Prod. Res. 52(11), 3185–3208 (2013)

    Article  Google Scholar 

  • Schwemmer, M.: Top 100 der Logistik Marktgrößen, Marktsegmente und Marktführer; eine Studie der Fraunhofer Arbeitsgruppe für Supply Chain Services SCS. 2016/2017. DVV Media Group GmbH, Hamburg (2016)

    Google Scholar 

  • Sonnessa, M.: Modelling and Simulation of Complex Systems. University of Torino, Italy (2004)

    Google Scholar 

  • Sprenger, R., Mönch, L.: a decision support system for cooperative transportation planning design, implementation, and performance assessment. Expert Syst. Appl. 41(11), 5125–5138 (2014)

    Article  Google Scholar 

  • Tako, A.A., Robinson, S.: The application of discrete event simulation and system dynamics in the logistics and supply chain context. Decis. Support Syst. 52(4), 802–815 (2012)

    Article  Google Scholar 

  • Vojdani, N., Erichsen, B., Lück, T.: Nutzung von Produktionsechtzeitdaten - Eine agentenbasierte Feinplanung mittels Simulation. Logist. J. Proc. 2017 (2017)

    Google Scholar 

  • Yang, Y., Pan, S., Ballot, E.: Freight transportation resilience enabled by physical internet. IFAC-PapersOnLine 50(1), 2278–2283 (2017)

    Article  Google Scholar 

Download references

Acknowledgments

This paper is a research result in context of the Leistungszentrum (Center of Excellence) Logistics & IT, an initiative of the Fraunhofer-Gesellschaft and the state of North Rhine-Westphalia, Germany.

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Correspondence to Moritz Poeting .

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Clausen, U., Brueggenolte, M., Kirberg, M., Besenfelder, C., Poeting, M., Gueller, M. (2019). Agent-Based Simulation in Logistics and Supply Chain Research: Literature Review and Analysis. In: Clausen, U., Langkau, S., Kreuz, F. (eds) Advances in Production, Logistics and Traffic. ICPLT 2019. Lecture Notes in Logistics. Springer, Cham. https://doi.org/10.1007/978-3-030-13535-5_4

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  • DOI: https://doi.org/10.1007/978-3-030-13535-5_4

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