IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v328y2026i2p633-645.html

The continuous roll-on roll-off dual cycling problem with tugs and driver-handled cargo units

Author

Listed:
  • Marquardt, Teresa
  • Heinold, Arne
  • Cleophas, Catherine
  • Meisel, Frank

Abstract

Roll-on roll-off vessels are a popular mode of transport in short-sea shipping. In this domain, appropriate stevedoring procedures are crucial to enhance efficiency. This includes dual cycling, where tugs simultaneously load and unload the vessel. Dual cycling reduces turnaround time, thereby giving the vessel more time to travel and allowing for slow steaming and reduced emissions.

Suggested Citation

  • Marquardt, Teresa & Heinold, Arne & Cleophas, Catherine & Meisel, Frank, 2026. "The continuous roll-on roll-off dual cycling problem with tugs and driver-handled cargo units," European Journal of Operational Research, Elsevier, vol. 328(2), pages 633-645.
    • Handle: RePEc:eee:ejores:v:328:y:2026:i:2:p:633-645
    DOI: 10.1016/j.ejor.2025.05.050
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221725004485
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2025.05.050?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Tongzon, Jose L., 1995. "Determinants of port performance and efficiency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 29(3), pages 245-252, May.
    2. Chandra, Saurabh & Christiansen, Marielle & Fagerholt, Kjetil, 2016. "Combined fleet deployment and inventory management in roll-on/roll-off shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 92(C), pages 43-55.
    3. Anne V. Goodchild & Carlos F. Daganzo, 2006. "Double-Cycling Strategies for Container Ships and Their Effect on Ship Loading and Unloading Operations," Transportation Science, INFORMS, vol. 40(4), pages 473-483, November.
    4. Jia, Beizhen & Tierney, Kevin & Reinhardt, Line Blander & Pahl, Julia, 2022. "Optimal dual cycling operations in roll-on roll-off terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    5. Li, Wenkai & Wu, Yong & Petering, M.E.H. & Goh, Mark & Souza, Robert de, 2009. "Discrete time model and algorithms for container yard crane scheduling," European Journal of Operational Research, Elsevier, vol. 198(1), pages 165-172, October.
    6. Arne Heinold & Teresa Marquardt & Frank Meisel & Catherine Cleophas, 2025. "Design and Implementation of a Data-Driven Instance Generator for Loading and Unloading RoRo-Ships," Lecture Notes in Operations Research, in: Guido Voigt & Malte Fliedner & Knut Haase & Wolfgang Brüggemann & Kai Hoberg & Joern Meissner (ed.), Operations Research Proceedings 2023, chapter 0, pages 233-239, Springer.
    7. Christos Kontovas & Harilaos N. Psaraftis, 2011. "Reduction of emissions along the maritime intermodal container chain: operational models and policies," Maritime Policy & Management, Taylor & Francis Journals, vol. 38(4), pages 451-469, March.
    8. Roy, Debjit & de Koster, René, 2018. "Stochastic modeling of unloading and loading operations at a container terminal using automated lifting vehicles," European Journal of Operational Research, Elsevier, vol. 266(3), pages 895-910.
    9. Thiago Noronha & Mauricio Resende & Celso Ribeiro, 2011. "A biased random-key genetic algorithm for routing and wavelength assignment," Journal of Global Optimization, Springer, vol. 50(3), pages 503-518, July.
    10. Chung-Yee Lee & Ming Liu & Chengbin Chu, 2015. "Optimal Algorithm for the General Quay Crane Double-Cycling Problem," Transportation Science, INFORMS, vol. 49(4), pages 957-967, November.
    11. Tang, Lixin & Zhao, Jiao & Liu, Jiyin, 2014. "Modeling and solution of the joint quay crane and truck scheduling problem," European Journal of Operational Research, Elsevier, vol. 236(3), pages 978-990.
    12. Tiago A. Santos & C. Guedes Soares, 2017. "Methodology for ro-ro ship and fleet sizing with application to short sea shipping," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(7), pages 859-881, October.
    13. James C. Bean, 1994. "Genetic Algorithms and Random Keys for Sequencing and Optimization," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 154-160, May.
    14. Yuzhe Zhao & Peiyun Peng & Jingmiao Zhou & Yadong Wang, 2025. "Heuristic algorithm for integrated ship scheduling, routing and stowage problem in multi-vessel roll-on/roll-off shipping," Journal of Heuristics, Springer, vol. 31(1), pages 1-40, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fowler, John W. & Mönch, Lars, 2022. "A survey of scheduling with parallel batch (p-batch) processing," European Journal of Operational Research, Elsevier, vol. 298(1), pages 1-24.
    2. Andrade, Carlos E. & Toso, Rodrigo F. & Gonçalves, José F. & Resende, Mauricio G.C., 2021. "The Multi-Parent Biased Random-Key Genetic Algorithm with Implicit Path-Relinking and its real-world applications," European Journal of Operational Research, Elsevier, vol. 289(1), pages 17-30.
    3. Dalila B. M. M. Fontes & S. Mahdi Homayouni, 2023. "A bi-objective multi-population biased random key genetic algorithm for joint scheduling quay cranes and speed adjustable vehicles in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 241-268, March.
    4. F. Stefanello & L. S. Buriol & M. J. Hirsch & P. M. Pardalos & T. Querido & M. G. C. Resende & M. Ritt, 2017. "On the minimization of traffic congestion in road networks with tolls," Annals of Operations Research, Springer, vol. 249(1), pages 119-139, February.
    5. Soares, Leonardo Cabral R. & Carvalho, Marco Antonio M., 2020. "Biased random-key genetic algorithm for scheduling identical parallel machines with tooling constraints," European Journal of Operational Research, Elsevier, vol. 285(3), pages 955-964.
    6. Ghorashi Khalilabadi, S. M. & Roy, D. & de Koster, M.B.M., 2022. "A Data-driven Approach to Enhance Worker Productivity by Optimizing Facility Layout," ERIM Report Series Research in Management ERS-2022-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Gonçalves, José Fernando & Wäscher, Gerhard, 2020. "A MIP model and a biased random-key genetic algorithm based approach for a two-dimensional cutting problem with defects," European Journal of Operational Research, Elsevier, vol. 286(3), pages 867-882.
    8. Fernando Stefanello & Vaneet Aggarwal & Luciana S. Buriol & Mauricio G. C. Resende, 2019. "Hybrid algorithms for placement of virtual machines across geo-separated data centers," Journal of Combinatorial Optimization, Springer, vol. 38(3), pages 748-793, October.
    9. Alfredo Lima & Luiz Satoru Ochi & Bruno Nogueira & Rian G. S. Pinheiro, 2025. "Biased random-key genetic algorithms for the weighted minimum broadcast time problem," Annals of Operations Research, Springer, vol. 349(3), pages 1749-1783, June.
    10. Yuzhe Zhao & Peiyun Peng & Jingmiao Zhou & Yadong Wang, 2025. "Heuristic algorithm for integrated ship scheduling, routing and stowage problem in multi-vessel roll-on/roll-off shipping," Journal of Heuristics, Springer, vol. 31(1), pages 1-40, March.
    11. R. B. Damm & A. A. Chaves & J. A. Riveaux & D. P. Ronconi, 2025. "Scheduling technicians and tasks through an adaptive multi-objective biased random-key genetic algorithm," Annals of Operations Research, Springer, vol. 346(2), pages 945-980, March.
    12. Dragović, Branislav & Dragović, Andro & Dulebenets, Maxim A., 2025. "The quay crane operation problem at marine container terminals: bibliometric analysis, emerging trends, and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 201(C).
    13. Rafael A. Melo & Celso C. Ribeiro & Jose A. Riveaux, 2025. "A biased random-key genetic algorithm for the minimum quasi-clique partitioning problem," Annals of Operations Research, Springer, vol. 351(1), pages 575-607, August.
    14. Fontes, Dalila B.M.M. & Homayouni, S. Mahdi & Gonçalves, José F., 2023. "A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1140-1157.
    15. Jia, Beizhen & Tierney, Kevin & Reinhardt, Line Blander & Pahl, Julia, 2022. "Optimal dual cycling operations in roll-on roll-off terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    16. Geiza Silva & André Leite & Raydonal Ospina & Víctor Leiva & Jorge Figueroa-Zúñiga & Cecilia Castro, 2023. "Biased Random-Key Genetic Algorithm with Local Search Applied to the Maximum Diversity Problem," Mathematics, MDPI, vol. 11(14), pages 1-11, July.
    17. Pinto, Bruno Q. & Ribeiro, Celso C. & Rosseti, Isabel & Plastino, Alexandre, 2018. "A biased random-key genetic algorithm for the maximum quasi-clique problem," European Journal of Operational Research, Elsevier, vol. 271(3), pages 849-865.
    18. Edson Ticona-Zegarra & Rafael CS Schouery & Leandro A Villas & Flávio K Miyazawa, 2018. "Improved continuous enhancement routing solution for energy-aware data aggregation in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 14(5), pages 15501477187, May.
    19. Li, Xueping & Zhang, Kaike, 2018. "Single batch processing machine scheduling with two-dimensional bin packing constraints," International Journal of Production Economics, Elsevier, vol. 196(C), pages 113-121.
    20. Bruno Q. Pinto & Celso C. Ribeiro & Isabel Rosseti & Thiago F. Noronha, 2020. "A biased random-key genetic algorithm for routing and wavelength assignment under a sliding scheduled traffic model," Journal of Global Optimization, Springer, vol. 77(4), pages 949-973, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:328:y:2026:i:2:p:633-645. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.