Skip to main content
SpringerLink
Log in

Innovations in Self-Organizing Maritime Logistics

  • Chapter
  • First Online:
Arctic Maritime Logistics

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

  • 577 Accesses

Abstract

Maritime logistics, where competition is fierce, is in dire need of efficient modes of transport. Automated systems are inevitable, ultimately developing themselves into self-organizing logistic systems. This chapter highlights some promising recent innovations in that area. As innovative automated systems, we discuss: (i) autonomous yard tractors, (ii) unmanned cargo aircraft, (iii) truck platooning, (iv) autonomous vessels, and (v) extended gates. To control these systems, we discuss innovative forms of intelligent decision-making, namely: (i) distributed planning, (ii) matching platforms, (iii) cooperation between barges and terminals, (iv) shared services and fair optimization, and (v) gamification in container supply chains. Moreover, we design a unifying framework that classifies automated systems within maritime logistics according to their potential to grow out to self-organizing systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alacam, S., & Sencer, A. (2021). Using blockchain technology to foster collaboration among shippers and carriers in the trucking industry: A design science research approach. Logistics, 5, 37. https://doi-org.ezproxy2.utwente.nl/10.3390/logistics5020037

  • Alam, A., Besselink, B., Turri, V., Martensson, J., & Johansson, K. (2015). Heavy-duty vehicle platooning for sustainable freight transportation: A cooperative method to enhance safety and efficiency. IEEE Control Systems, 35(6), 34–56.

    Article  Google Scholar 

  • Brunetti, M., Mes, M., & van Heuveln, J. (2020). A general framework for smart yards. In K.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, & R. Thiesing (Eds.), Proceedings of the 2020 Winter Simulation Conference (pp. 2743–2754). Institute of Electrical and Electronics Engineers, Inc.

    Google Scholar 

  • Dai, B., & Chen, H. (2012). Profit allocation mechanisms for carrier collaboration in pickup and delivery service. Computers & Industrial Engineering, 62, 633–643.

    Article  Google Scholar 

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982–1003.

    Article  Google Scholar 

  • Douma, A. M., Schutten, J. M. J., & Schuur, P. C. (2009). Waiting profiles: An efficient protocol for enabling distributed planning of container barge rotations along terminals in the Port of Rotterdam. Transportation Research Part C, 17, 133–148.

    Article  Google Scholar 

  • Douma, A. M., Schuur, P. C., & Schutten, J. M. J. (2011). Aligning barge and terminal operations using service-time profiles. Flexible Services and Manufacturing Journal, 23, 385–421.

    Article  Google Scholar 

  • Douma, A. M., Van Hillegersberg, J., & Schuur, P. C. (2012). Design and evaluation of a simulation game to introduce a multi-agent system for barge handling in a seaport. Decision Support Systems, 53(3), 465–472.

    Article  Google Scholar 

  • Fossati, F., Hoteit, S., Moretti, S., & Secci, S. (2018). Fair resource allocation in systems with complete information sharing. IEEE/ACM Transactions on Networking, 26(6), 2801–2814.

    Article  Google Scholar 

  • Fotuhi, F., Huynh, N., Vidal, J. M., & Xie, Y. (2013). Modeling yard crane operators as reinforcement learning agents. Research in Transportation Economics, 42(1), 3–12.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Gerrits, B., Mes, M., & Schuur, P. (2020). Mixing it up: Simulation of mixed traffic container terminals. In K.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, & R. Thiesing (Eds.), Proceedings of the 2020 Winter Simulation Conference (pp. 1384–1395). Institute of Electrical and Electronics Engineers, Inc.

    Google Scholar 

  • Gerrits, B., Schuur, P., Ilin, I., & Kalyazina, S. (2019). Mixing automated with non-automated yard traffic in container terminals: A digital transition. In Proceedings of the International Conference on Digital Technologies in Logistics and Infrastructure (ICDTLI 2019) (pp. 397–401). Atlantis Press.

    Google Scholar 

  • Gu, Y., Góez, J. C., Guajardo, M., & Wallace, S. W. (2021). Autonomous vessels: State of the art and potential opportunities in logistics. International Transactions in Operational Research, 28(1), 1706–1739.

    Article  Google Scholar 

  • Heerkens, H. (2017). Unmanned cargo aircraft: From anywhere to everywhere. Engineering & Technology Reference. https://doi-org.ezproxy2.utwente.nl/10.1049/etr.2017.0009

  • Kongsberg. (2018). Autonomous ship project, key facts about YARA Birkeland. https://www.km.kongsberg.com/ks/web/nokbg0240.nsf/AllWeb/4B8113B707A50A4FC125811D00407045?OpenDocument.

  • Kretschmann, L., Burmeister, H. C., & Jahn, C. (2017). Analyzing the economic benefit of unmanned autonomous ships: An exploratory cost-comparison between an autonomous and a conventional bulk carrier. Research in Transportation Business & Management, 25, 76–86.

    Article  Google Scholar 

  • Li, K., & Ioannou, P. (2004). Modeling of traffic flow of automated vehicles. IEEE Transactions on Intelligent Transportation Systems, 5(2), 99–113.

    Article  Google Scholar 

  • Liebeck, R. H. (2004). Design of the blended wing body subsonic transport. Journal of Aircraft, 41(1), 1–24.

    Article  Google Scholar 

  • Marinica, N. E., Capiluppi, M., Rogge, J. A., Segala, R., & Boel, R. (2012, June 6–8). Distributed collision avoidance for autonomous vehicles: World automata representation. In IFAC Proceedings Volumes (IFAC-PapersOnline) (pp. 216–221). IFAC.

    Google Scholar 

  • Melis, M., Miller, I., Kentrop, M., Van Eck, B., Leenaarts, M., Schut, M., & Treur, J. (2003). Distributed rotation planning for container barges in the Port of Rotterdam. In T. Verduijn, & B. Loo (Eds.), Intelligent logistics concepts (pp 101–116). Eburon Publishers.

    Google Scholar 

  • Merk, O., & Notteboom, T. (2015). Port Hinterland connectivity. International Transport Forum Discussion Paper No. 2015-13.

    Google Scholar 

  • Mes, M., & Douma, A. (2016). Agent-based support for container terminals to make appointments with barges. In A. Paias, M. Ruthmair, & S. Voß (Eds.), Computational logistics (pp. 80–95). Springer International Publishing.

    Google Scholar 

  • Mes, M., & Gerrits, B. (2019). Multi-agent systems. In Lecture notes in logistics. Springer International Publishing. https://doi-org.ezproxy2.utwente.nl/10.1007/978-3-319-92447-2_27.

  • Mes, M., van der Heijden, M., & van Harten, A. (2007). Comparison of agent-based scheduling to look-ahead heuristics for real-time transportation problems. European Journal of Operational Research, 181(1), 59–75. https://doi-org.ezproxy2.utwente.nl/10.1016/j.ejor.2006.02.051

  • Montoya-Torres, J. R., Franco, J. L., Isaza, S. N., Jimnez, H. F., & Herazo-Padilla, N. (2015). A literature review on the vehicle routing problem with multiple depots. Computers & Industrial Engineering, 79, 115–129.

    Article  Google Scholar 

  • Nabais, J. L., Negenborn, R. R., Carmona Benitez, R. B., & Botto, M. A. (2013, October 6–9). Setting cooperative relations among terminals at seaports using a multi-agent system. In IEEE Conference on Intelligent Transportation Systems Proceedings (pp. 1731–1736). ITSC.

    Google Scholar 

  • Parthibaraj, C. S., Palaniappan, P., Gunasekaran, A., & Subramanian, N. (2017). Multi-agent system with iterative auction mechanism for master bay plan problem in marine logistics. Maritime Policy & Management, 44(6), 705–726.

    Article  Google Scholar 

  • Robinson, T., Chan, E., & Coelingh, E. (2010). Operating platoons on public motorways: An introduction to the SARTRE platooning programme. In Proceedings of the 17th ITS world congress.

    Google Scholar 

  • Rolls-Royce. (2018). Rolls-Royce and Finferries demonstrate world’s first fully autonomous ferry. https://www.rollsroyce.com/media/press-releases/2018/03-12-2018-rr-and-finferries-demonstrate-worlds-first-fully-autonomousferry.aspx

  • Saglietto, L. (2013). Towards a classification of fourth party logistics (4PL). Universal Journal of Industrial and Business Management, 1(3), 104–116.

    Article  Google Scholar 

  • Schut, M., Kentrop, M., Leenaarts, M., Melis, M., & Miller, I. (2004). Approach: Decentralised rotation planning for container barges. In Proceedings of the 16th European conference on artificial intelligence.

    Google Scholar 

  • Sharif, O., & Huynh, N. (2012). Yard crane scheduling at container terminals: A comparative study of centralized and decentralized approaches. Maritime Economics & Logistics, 14(2), 139–161.

    Article  Google Scholar 

  • Sinha, A., & Anastasopoulos, A. (2017). Incentive mechanisms for fairness among strategic agents. IEEE Journal on Selected Areas in Communications, 35(2), 288–301.

    Article  Google Scholar 

  • Souravlies, D., Dafnomilis, I., Ley, J., Assbrock, G., Negenborn, R. R., & Scott, D. L. (2020). Design framework for a modular floating container terminal. Frontiers in Marine Science, 7, 1–17.

    Article  Google Scholar 

  • Taleb, T., Benslimane, A., & Letaief, K. (2010). Toward an effective risk-conscious and collaborative vehicular collision avoidance system. IEEE Transactions on Vehicular Technology, 59(3), 1474–1486.

    Article  Google Scholar 

  • Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39, 273–315.

    Article  Google Scholar 

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quartely, 27, 425–478.

    Article  Google Scholar 

  • Wibowo, R. A., Hidayatno, A., Komarudin, K., & Moeis, A. O. (2015). Simulating port expansion plans using agent based modelling. International Journal of Technology, 6(5), 864–871.

    Article  Google Scholar 

  • Zheng, S., & Negenborn, R. R. (2014). Centralization or decentralization: A comparative analysis of port regulation modes. Transportation Research Part E: Logistics and Transportation Review, 69, 21–40.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering and Business Information Systems, University of Twente, Enschede, The Netherlands

    Berry Gerrits & Peter Schuur

Authors
  1. Berry Gerrits
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peter Schuur
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Berry Gerrits .

Editor information

Editors and Affiliations

  1. Peter the Great St.Petersburg Polytechnic University, St. Petersburg, Russia

    Igor Ilin

  2. Atlântica – Instituto Universitário, Barcarena, Portugal

    Tessaleno Devezas

  3. Hamburg University of Technology, Hamburg, Germany

    Carlos Jahn

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gerrits, B., Schuur, P. (2022). Innovations in Self-Organizing Maritime Logistics. In: Ilin, I., Devezas, T., Jahn, C. (eds) Arctic Maritime Logistics. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-030-92291-7_11

Download citation

Publish with us

Policies and ethics

Search

Navigation