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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
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)
Ait-Kadi, D., Chouinard, M., Marcotte, S., Riopel, D.: Sustainable Reverse Logistics Network Engineering and Management. ISTE, Wiley, London, Hoboken (2012)
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)
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)
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)
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)
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)
Chopra, S., Meindl, P.: Supply Chain Management Strategy, Planning, and Operation, 6th Global edn. Pearson, Boston (2016)
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)
Femerling, J.C., Gleißner, H.: Logistics Basics - Exercises - Case Studies. Springer, Cham (2013). (Springer Texts in Business and Economics)
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)
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)
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)
Heath, B.L., Hill, R.R.: Some insights into the emergence of agent-based modelling. J. Simul. 4(3), 163–169 (2010)
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)
Klügl, F., Bazzan, A.L.C.: Agent-based modeling and simulation. AIMag 33(3), 29 (2012)
Krejci, C.C.: Hybrid simulation modeling for humanitarian relief chain coordination. J. Hum. Logist. Supply Chain. Manag. 5(3), 325–347 (2015)
Law, A.M.: Simulation Modeling and Analysis, 5th edn. McGraw-Hill, New York (2015)
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)
Macal, C.M.: Everything you need to know about agent-based modelling and simulation. J. Simul. 10(2), 144–156 (2016)
Macal, C.M., North, M.J.: Tutorial on agent-based modelling and simulation. J. Simul. 4(3), 151–162 (2010)
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)
Pegden, C.D.: Advanced tutorial: overview of simulation world views. In: Proceedings of the 2010 Winter Simulation Conference, pp. 210–215 (2010)
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)
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)
Sonnessa, M.: Modelling and Simulation of Complex Systems. University of Torino, Italy (2004)
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)
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)
Vojdani, N., Erichsen, B., Lück, T.: Nutzung von Produktionsechtzeitdaten - Eine agentenbasierte Feinplanung mittels Simulation. Logist. J. Proc. 2017 (2017)
Yang, Y., Pan, S., Ballot, E.: Freight transportation resilience enabled by physical internet. IFAC-PapersOnLine 50(1), 2278–2283 (2017)
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-13535-5_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-13534-8
Online ISBN: 978-3-030-13535-5
eBook Packages: EngineeringEngineering (R0)