A Self-Adaptive Monte Carlo Tree Search Algorithm for Generalized Quay Crane Scheduling Problem

Published Online:https://doi.org/10.1287/trsc.2025.0016

References

  • Abou Kasm O, Diabat A (2019) The quay crane scheduling problem with non-crossing and safety clearance constraints: An exact solution approach. Comput. Oper. Res. 107:189–199.CrossrefGoogle Scholar
  • Abou Kasm O, Diabat A (2020) Next-generation quay crane scheduling. Transportation Res. Part C Emerging Tech. 114:694–715.CrossrefGoogle Scholar
  • Al-Dhaheri N, Diabat A (2017) A Lagrangian relaxation-based heuristic for the multi-ship quay crane scheduling problem with ship stability constraints. Ann. Oper. Res. 248:1–24.CrossrefGoogle Scholar
  • Al-Dhaheri N, Jebali A, Diabat A (2016) The quay crane scheduling problem with nonzero crane repositioning time and vessel stability constraints. Comput. Indust. Engrg. 94:230–244.CrossrefGoogle Scholar
  • Bierwirth C, Meisel F (2010) A survey of berth allocation and quay crane scheduling problems in container terminals. Eur. J. Oper. Res. 202(3):615–627.CrossrefGoogle Scholar
  • Bierwirth C, Meisel F (2015) A follow-up survey of berth allocation and quay crane scheduling problems in container terminals. Eur. J. Oper. Res. 244(3):675–689.CrossrefGoogle Scholar
  • Browne CB, Powley E, Whitehouse D, Lucas SM, Cowling PI, Rohlfshagen P, Tavener S, Perez D, Samothrakis S, Colton S (2012) A survey of Monte Carlo tree search methods. IEEE Trans. Comput. Intelligence AI Games 4(1):1–43.CrossrefGoogle Scholar
  • Chen JH, Bierlaire M (2017) The study of the unidirectional quay crane scheduling problem: Complexity and risk-aversion. Eur. J. Oper. Res. 260(2):613–624.CrossrefGoogle Scholar
  • Daganzo CF (1989) The crane scheduling problem. Transportation Res. Part B Methodological 23(3):159–175.CrossrefGoogle Scholar
  • Dik G, Kozan E (2017) A flexible crane scheduling methodology for container terminals. Flexible Services Manufacturing J. 29(1):64–96.CrossrefGoogle Scholar
  • Hu C, Tang J, Hu J, Wang Y, Li Z, Zeng J, Han C (2025) Dynamic partitioning of heterogeneously loaded road networks: A two-level regionalization scheme with Monte Carlo tree search. Transportation Res. Part C Emerging Tech. 180:105341.CrossrefGoogle Scholar
  • Huang SY, Li Y (2018) A bounded two-level dynamic programming algorithm for quay crane scheduling in container terminals. Comput. Indust. Engrg. 123:303–313.CrossrefGoogle Scholar
  • Jooken J, Leyman P, Wauters T, De Causmaecker P (2023) Exploring search space trees using an adapted version of Monte Carlo tree search for combinatorial optimization problems. Comput. Oper. Res. 150:106070.CrossrefGoogle Scholar
  • Kandula S, Roy D, Akartunalı K (2025) A machine learning approach to solve the e-commerce box-sizing problem. Production Oper. Management 34(6):1326–1345.CrossrefGoogle Scholar
  • Kocsis L, Szepesvári C (2006) Bandit based Monte-Carlo planning. Fürnkranz J, Scheffer T, Spiliopoulou M, eds. Machine Learning: ECML 2006 (Springer, Berlin), 282–293.Google Scholar
  • Li Y, Li X, Zhang C, Wu T (2024) Decomposition algorithms for the robust unidirectional quay crane scheduling problems. Comput. Oper. Res. 167:106670.CrossrefGoogle Scholar
  • Lim A, Rodrigues B, Xu Z (2007) A m-parallel crane scheduling problem with a non-crossing constraint. Naval Res. Logist. 54(2):115–127.CrossrefGoogle Scholar
  • Liu X, Peng Y, Zhang G, Zhou R (2025) An efficient node selection policy for Monte Carlo tree search with neural networks. INFORMS J. Comput. 37(4):785–807.LinkGoogle Scholar
  • Lizotte DJ, Laber EB (2016) Multi-objective Markov decision processes for data-driven decision support. J. Machine Learn. Res. 17(210):1–28.Google Scholar
  • Ma S, Li H, Zhu N, Fu C (2021) Stochastic programming approach for unidirectional quay crane scheduling problem with uncertainty. J. Scheduling 24:137–174.CrossrefGoogle Scholar
  • Mańdziuk J, Nejman C (2015) UCT-based approach to capacitated vehicle routing problem. Rutkowski L, Korytkowski M, Scherer R, Tadeusiewicz R, Zadeh LA, Zurada JM, eds. Artificial Intelligence and Soft Computing (Springer International Publishing, Cham, Switzerland), 679–690.CrossrefGoogle Scholar
  • Meisel F, Bierwirth C (2011) A unified approach for the evaluation of quay crane scheduling models and algorithms. Comput. Oper. Res. 38(3):683–693.CrossrefGoogle Scholar
  • Msakni MK, Diabat A, Rabadi G, Al-Salem M, Kotachi M (2018) Exact methods for the quay crane scheduling problem when tasks are modeled at the single container level. Comput. Oper. Res. 99:218–233.CrossrefGoogle Scholar
  • Rodrigues F, Agra A (2024) Handling uncertainty in the quay crane scheduling problem: A unified distributionally robust decision model. Internat. Trans. Oper. Res. 31(2):721–748.CrossrefGoogle Scholar
  • Silver D, Huang A, Maddison CJ, Guez A, Sifre L, Van Den Driessche G, Schrittwieser J, et al. (2016) Mastering the game of Go with deep neural networks and tree search. Nature 529(7587):484–489.CrossrefGoogle Scholar
  • Sun D, Tang L, Baldacci R (2019) A Benders decomposition-based framework for solving quay crane scheduling problems. Eur. J. Oper. Res. 273(2):504–515.CrossrefGoogle Scholar
  • Sun D, Tang L, Baldacci R, Chen Z (2024) A decomposition method for the group-based quay crane scheduling problem. INFORMS J. Comput. 36(2):543–570.LinkGoogle Scholar
  • Sun D, Tang L, Baldacci R, Lim A (2021) An exact algorithm for the unidirectional quay crane scheduling problem with vessel stability. Eur. J. Oper. Res. 291(1):271–283.CrossrefGoogle Scholar
  • Wang G, Pu H, Song T, Schonfeld P, Li W, Zhang H, Peng L, Hu J, Qiao J (2024) A 3D Monte Carlo tree search method for railway alignment optimization. Appl. Soft Comput. 151:111158.CrossrefGoogle Scholar
  • Wu L, Ma W (2017) Quay crane scheduling with draft and trim constraints. Transportation Res. Part E Logist. Transportation Rev. 97:38–68.CrossrefGoogle Scholar
  • Yu S, Wang S, Zhen L (2017) Quay crane scheduling problem with considering tidal impact and fuel consumption. Flexible Services Manufacturing J. 29:345–368.CrossrefGoogle Scholar
  • Zhang Z, Liu M, Lee CY, Wang J (2018) The quay crane scheduling problem with stability constraints. IEEE Trans. Automation Sci. Engrg. 15(3):1399–1412.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.