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Coordinated scheduling problems for sustainable production of container terminals: a literature review

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Abstract

A container terminal plays a significant role in global supply chain. Coordinated scheduling is one of the most important issues for sustainable development of container terminals. This research provides an in-depth survey of the coordinated scheduling for container terminals in order to identify existing research streams for future investigations. Researches on the coordinated scheduling of container terminals which are published between 2010 and 2021 are reviewed and classified. Related coordinated scheduling models and solution methods are analyzed. Research gaps and future directions are also lighted up. This will help new researchers quickly understanding the distribution of researches on these fields. The findings are important for both research and practice perspectives.

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References

  • Agra, A., & Oliveira, M. (2018). Mip approaches for the integrated berth allocation and quay crane assignment and scheduling problem. European Journal of Operational Research, 264(1), 138–148.

    MathSciNet  Google Scholar 

  • Al-Dhaheri, N., & Diabat, A. (2017). A Lagrangian relaxation-based heuristic for the multi-ship quay crane scheduling problem with ship stability constraints. Annals of Operations Research, 248(1–2), 1–24.

    MathSciNet  Google Scholar 

  • Assadipour, G., Ke, G. Y., & Verma, M. (2014). An analytical framework for integrated maritime terminal scheduling problems with time windows. Expert Systems with Applications, 41(16), 7415–7424.

    Google Scholar 

  • Azevedo, A. T., de Salles Neto, L. L., Chaves, A. A., & Moretti, A. C. (2018). Solving the 3D stowage planning problem integrated with the quay crane scheduling problem by representation by rules and genetic algorithm. Applied Soft Computing, 65, 495–516.

    Google Scholar 

  • Bierwirth, C., & Meisel, F. (2010). A survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research, 202(3), 615–627.

    MathSciNet  Google Scholar 

  • Bierwirth, C., & Meisel, F. (2015). A follow-up survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research, 244(3), 675–689.

    MathSciNet  Google Scholar 

  • BP (2021). Statistical review of world energy 2021. Technical report, BP.

  • Cao, J. X., Lee, D.-H., Chen, J. H., & Shi, Q. (2010). The integrated yard truck and yard crane scheduling problem: Benders’ decomposition-based methods. Transportation Research Part E: Logistics and Transportation Review, 46(3), 344–353.

    Google Scholar 

  • Carlo, H. J., Vis, I. F. A., & Roodbergen, K. J. (2014). Storage yard operations in container terminals: Literature overview, trends, and research directions. European Journal of Operational Research, 235(2), 412–430.

    Google Scholar 

  • Castilla-Rodriguez, I., Exposito-Izquierdo, C., Melian-Batista, B., Aguilar, R. M., & Marcos Moreno-Vega, J. (2020). Simulation-optimization for the management of the transshipment operations at maritime container terminals. Expert Systems with Applications, 139, 112852.

    Google Scholar 

  • Chang, D., Jiang, Z., Yan, W., & He, J. (2010). Integrating berth allocation and quay crane assignments. Transportation Research Part E-Logistics and Transportation Review, 46(6), 975–990.

    Google Scholar 

  • Chang, Y. M., Zhu, X. N., & Haghani, A. (2019). Modeling and solution of joint storage space allocation and handling operation for outbound containers in rail-water intermodal container terminals. IEEE Access, 7, 55142–55158.

    Google Scholar 

  • Chang, Y. M., Zhu, X. N., Yan, B. C., & Wang, L. (2019). Integrated scheduling of handling operations in railway container terminals. Transportation Letters-the International Journal Of Transportation Research, 11(7), 402–412.

    Google Scholar 

  • Chen, G., Govindan, K., Yang, Z.-Z., Choi, T.-M., & Jiang, L. (2013). Terminal appointment system design by non-stationary m(t)/e-k/c(t) queueing model and genetic algorithm. International Journal of Production Economics, 146(2), 694–703.

    Google Scholar 

  • Chen, L., Langevin, A., & Zhiqiang, L. (2013). Integrated scheduling of crane handling and truck transportation in a maritime container terminal. European Journal of Operational Research, 225(1), 142–152.

    Google Scholar 

  • Chen, C., Zeng, Q., & Zhang, Z. (2012). An integrating scheduling model for mixed cross-operation in container terminals. Transport, 27(4), 405–413.

    CAS  Google Scholar 

  • Choe, R., Cho, H., Park, T., & Ryu, K. R. (2012). Queue-based local scheduling and global coordination for real-time operation control in a container terminal. Journal of Intelligent Manufacturing, 23(6), 2179–2182.

    Google Scholar 

  • Correcher, J. F., & Alvarez-Valdes, R. (2017). A biased random-key genetic algorithm for the time-invariant berth allocation and quay crane assignment problem. Expert Systems with Applications, 89, 112–128.

    Google Scholar 

  • Covic, F. (2017). Re-marshalling in automated container yards with terminal appointment systems. Flexible Services and Manufacturing Journal, 29(3–4), 433–503.

    Google Scholar 

  • Diabat, A., & Theodorou, E. (2014). An integrated quay crane assignment and scheduling problem. Computers & Industrial Engineering, 73(1), 115–123.

    Google Scholar 

  • Dkhil, H., Yassine, A., & Chabchoub, H. (2018). Multi-objective optimization of the integrated problem of location assignment and straddle carrier scheduling in maritime container terminal at import. Journal of the Operational Research Society, 69(2), 247–269.

    Google Scholar 

  • Duan, J., Liu, Y., Zhang, Q., & Qin, J. (2021). Combined configuration of container terminal berth and quay crane considering carbon cost. Mathematical Problems in Engineering, 2021, 1–16.

    Google Scholar 

  • Dung, D. N. A., Nielsen, I. E., Chen, G., & Nielsen, P. (2016). A simulation-based genetic algorithm approach for reducing emissions from import container pick-up operation at container terminal. Annals of Operations Research, 242(2), 285–301.

    MathSciNet  Google Scholar 

  • Fan, H., Ren, X., Guo, Z., & Li, Y. (2019). Truck scheduling problem considering carbon emissions under truck appointment system. Sustainability, 11(22), 6256.

    Google Scholar 

  • Fereidoonian, F., & Mirzazadeh, A. (2011). A genetic algorithm for the integrated scheduling model of a container-handling system in a maritime terminal. Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment, 226(1), 62–77.

    Google Scholar 

  • Gao, Y., Chang, D., Yuan, J., & Liang, C. (2023). Scheduling of yard truck considering loading and unloading simultaneously in an underground container logistics system. Transportation Research Record, 2677(2), 246–263.

    Google Scholar 

  • Geerlings, H., & van Duin, R. (2011). A new method for assessing co2-emissions from container terminals: A promising approach applied in Rotterdam. Journal of Cleaner Production, 19(6–7), 657–666.

    Google Scholar 

  • Giallombardo, G., Moccia, L., Salani, M., & Vacca, I. (2010). Modeling and solving the tactical berth allocation problem. Transportation Research Part B-Methodological, 44(2), 232–245.

    Google Scholar 

  • Gomez, R., Camarero, A., & Molina, R. (2016). Development of a vessel-performance forecasting system: Methodological framework and case study. Journal of Waterway Port Coastal and Ocean Engineering, 142(2), 04015016.

    Google Scholar 

  • Han, X. L., Gong, X., & Jo, J. (2015). A new continuous berth allocation and quay crane assignment model in container terminal. Computers & Industrial Engineering, 89, 15–22.

    Google Scholar 

  • He, J., Huang, Y., & Yan, W. (2015). Yard crane scheduling in a container terminal for the trade-off between efficiency and energy consumption. Advanced Engineering Informatics, 29(1), 59–75.

    Google Scholar 

  • Hendriks, M. P. M., Lefeber, E., & Udding, J. T. (2013). Simultaneous berth allocation and yard planning at tactical level. OR Spectrum, 35(2), 441–456.

    MathSciNet  Google Scholar 

  • Homayouni, S. M., Tang, S. H., & Motlagh, O. (2014). A genetic algorithm for optimization of integrated scheduling of cranes, vehicles, and storage platforms at automated container terminals. Journal of Computational and Applied Mathematics, 270, 545–556.

    MathSciNet  Google Scholar 

  • Hsu, H. P., Chiang, T. L., Wang, C. N., Fu, H. P., & Chou, C. C. (2019). A hybrid GA with variable quay crane assignment for solving berth allocation problem and quay crane assignment problem simultaneously. Sustainability, 11(7), 2018.

    Google Scholar 

  • Hsu, H. P., Wang, C. N., Chou, C. C., Lee, Y., & Wen, Y. F. (2017). Modeling and solving the three seaside operational problems using an object-oriented and timed predicate/transition net. Applied Sciences, 7(3), 218.

    Google Scholar 

  • Hsu, H. P., Wang, C. N., Fu, H. P., & Dang, T. T. (2021). Joint scheduling of yard crane, yard truck, and quay crane for container terminal considering vessel stowage plan: An integrated simulation-based optimization approach. Mathematics, 9(18), 2236.

    Google Scholar 

  • Hu, H. T., Chen, X. Z., & Zhang, S. (2019). Optimisation for quay crane scheduling problem under uncertainty using pso and ocba. International Journal Of Shipping And Transport Logistics, 11(2–3), 196–215.

    Google Scholar 

  • Im, H., Jiwon, Yu., & Lee, C. (2021). Truck appointment system for cooperation between the transport companies and the terminal operator at container terminals. Applied Sciences-Basel, 11(1), 168.

    CAS  Google Scholar 

  • Iris, C., & Lam, J. S. L. (2019). A review of energy efficiency in ports: Operational strategies, technologies and energy management systems. Renewable & Sustainable Energy Reviews, 112, 170–182.

    Google Scholar 

  • Iris, C., Pacino, D., & Ropke, S. (2017). Improved formulations and an adaptive large neighborhood search heuristic for the integrated berth allocation and quay crane assignment problem. Transportation Research Part E-Logistics and Transportation Review, 105, 123–147.

    Google Scholar 

  • Jaehn, F., & Kress, D. (2018). Scheduling cooperative gantry cranes with seaside and landside jobs. Discrete Applied Mathematics, 242, 53–68.

    MathSciNet  Google Scholar 

  • Jeong, B. J., & Kim, K. H. (2011). Scheduling operations of a rail crane and container deliveries between rail and port terminals. Engineering Optimization, 43(6), 597–613.

    Google Scholar 

  • Jiang, X. J., & Jin, J. G. (2017). A branch-and-price method for integrated yard crane deployment and container allocation in transshipment yards. Transportation Research Part B: Methodological, 98, 62–75.

    Google Scholar 

  • Jian, W., Zhu, J., & Zeng, Q. (2021). An Optimization Model of Integrated AGVs Scheduling and Container Storage Problems for Automated Container Terminal Considering Uncertainty. Symmetry, 13(10), 1904.

    ADS  Google Scholar 

  • Jiao, X., Zheng, F., Liu, M. & Xu, Y. (2018). Integrated berth allocation and time-variant quay crane scheduling with tidal impact in approach channel. In Discrete Dynamics in Nature and Society.

  • Jin, B. (2020). On the integer programming formulation for the relaxed restricted container relocation problem. European Journal of Operational Research, 281(2), 475–482.

    MathSciNet  Google Scholar 

  • Jonker, T., Duinkerken, M. B., Yorke-Smith, N., de Waal, A., & Negenborn, R. R. (2021). Coordinated optimization of equipment operations in a container terminal. Flexible Services and Manufacturing Journal, 33(2), 281–311.

    Google Scholar 

  • Karakas, S., Kirmizi, M., & Kocaoglu, B. (2021). Yard block assignment, internal truck operations, and berth allocation in container terminals: Introducing carbon-footprint minimisation objectives. Maritime Economics & Logistics, 23(4), 750–771.

    Google Scholar 

  • Kaveshgar, N., & Nathan, H. (2015). Integrated quay crane and yard truck scheduling for unloading inbound containers. International Journal of Production Economics, 159, 168–177.

    Google Scholar 

  • Kong, L. R., Ji, M. J., & Gao, Z. D. (2021). Joint optimization of container slot planning and truck scheduling for tandem quay cranes. European Journal of Operational Research, 293(1), 149–166.

    MathSciNet  Google Scholar 

  • Kress, D., Dornseifer, J., & Jaehn, F. (2019). An exact solution approach for scheduling cooperative gantry cranes. European Journal of Operational Research, 273(1), 82–101.

    MathSciNet  Google Scholar 

  • Lee, D.-H., Jin, J., & Chen, J. (2011). Integrated bay allocation and yard crane scheduling problem for transshipment containers. Transportation Research Record, 2222, 63–71.

    Google Scholar 

  • Legato, P., Mazza, R. M., & Gulli, D. (2014). Integrating tactical and operational berth allocation decisions via simulation-optimization. Computers & Industrial Engineering, 78, 84–94.

    Google Scholar 

  • Li, B., & He, Y. Q.(2021). Computational logistics for container terminal handling systems with deep learning. Computational Intelligence and Neuroscience, 2021 .

  • Li, N., Chen, G., Govindan, K., & Jin, Z. (2018). Disruption management for truck appointment system at a container terminal: A green initiative. Transportation Research Part D-Transport And Environment, 61, 261–273.

    Google Scholar 

  • Li, M.-W., Hong, W.-C., Geng, J., & Wang, J. (2017). Berth and quay crane coordinated scheduling using multi-objective chaos cloud particle swarm optimization algorithm. Neural Computing & Applications, 28(11), 3163–3182.

    Google Scholar 

  • Li, X., Otto, A., & Pesch, E. (2019). Solving the single crane scheduling problem at rail transshipment yards. Discrete Applied Mathematics, 264, 134–147.

    MathSciNet  CAS  Google Scholar 

  • Li, F., Sheu, J.-B., & Gao, Z.-Y. (2015). Solving the continuous berth allocation and specific quay crane assignment problems with quay crane coverage range. Transportation Science, 49(4), 968–989.

    Google Scholar 

  • Liu, C. (2020). Iterative heuristic for simultaneous allocations of berths, quay cranes, and yards under practical situations. Transportation Research Part E: Logistics and Transportation Review, 133, 101814.

    Google Scholar 

  • Liu, M., Lee, C.-Y., Zhang, Z., & Chu, C. (2016). Bi-objective optimization for the container terminal integrated planning. Transportation Research Part B-Methodological, 93, 720–749.

    Google Scholar 

  • Li, C., Zhiqiang, L., Han, X., Zhang, Y., & Wang, L. (2016). Integrated scheduling of a container handling system with simultaneous loading and discharging operations. Engineering Optimization, 48(3), 397–414.

    ADS  MathSciNet  Google Scholar 

  • Luo, J., Yue, W., & Mendes, A. B. (2016). Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal. Computers & Industrial Engineering, 94, 32–44.

    Google Scholar 

  • Lv, X., Jin, J. G., & Hu, H. (2020). Berth allocation recovery for container transshipment terminals. Maritime Policy & Management, 47(4), 558–574.

    Google Scholar 

  • Ma, M., Fan, H., Jiang, X., & Guo, Z. (2019). Truck arrivals scheduling with vessel dependent time windows to reduce carbon emissions. Sustainability, 11(22), 6410.

    Google Scholar 

  • Meisel, F., & Bierwirth, C. (2013). A framework for integrated berth allocation and crane operations planning in seaport container terminals. Transportation Science, 47(2), 131–147.

    Google Scholar 

  • Ning, T., Wang, Z., Zhang, P., & Gou, T. (2020). Integrated optimization of disruption management and scheduling for reducing carbon emission in manufacturing. Journal of Cleaner Production, 263, 1–8.

    Google Scholar 

  • Niu, B., Xie, T., Tan, L., Bi, Y., & Wang, Z. (2016). Swarm intelligence algorithms for yard truck scheduling and storage allocation problems. Neurocomputing, 188, 284–293.

    Google Scholar 

  • Niu, Y., Yu, F., Yao, H., & Yang, Y. (2022). Multi-equipment coordinated scheduling strategy of U-shaped automated container terminal considering energy consumption. Computers & Industrial Engineering, 174, 108804.

    Google Scholar 

  • Pang, K.-W., & Liu, J. (2014). An integrated model for ship routing with transshipment and berth allocation. IIE Transactions, 46(12), 1357–1370.

    Google Scholar 

  • Pani, C., Fadda, P., Fancello, G., Frigau, L., & Mola, F. (2014). A data mining approach to forecast late arrivals in a transhipment container terminal. Transport, 29(2), 175–184.

    Google Scholar 

  • Pani, C., Vanelslander, T., Fancello, G., & Cannas, M. (2015). Prediction of late/early arrivals in container terminals—A qualitative approach. European Journal of Transport and Infrastructure Research, 15(4), 536–550.

    Google Scholar 

  • Pan, J., Yinfeng, X., & Zhang, G. (2018). Online integrated allocation of berths and quay cranes in container terminals with 1-lookahead. Journal Of Combinatorial Optimization, 36(2), 617–636.

    MathSciNet  Google Scholar 

  • Peng, Y., Wang, W., Liu, K., Li, X., & Tian, Q. (2018). The impact of the allocation of facilities on reducing carbon emissions from a green container terminal perspective. Sustainability, 10(6), 1813.

    Google Scholar 

  • Phan, M. H., & Kim, K. H. (2016). Collaborative truck scheduling and appointments for trucking companies and container terminals. Transportation Research Part B: Methodological, 86, 37–50.

    Google Scholar 

  • Pjevcevic, D., Nikolic, M., Vidic, N., & Vukadinovic, K. (2017). Data envelopment analysis of AGV fleet sizing at a port container terminal. International Journal of Production Research, 55(14), 4021–4034.

    Google Scholar 

  • Pratap, S., Nayak, A., Kumar, A., Cheikhrouhou, N., & Tiwari, M. K. (2017). An integrates decision support system for berth ana snip unloader allocation in bulk material handing port. Computers & Industrial Engineering, 106, 386–399.

    Google Scholar 

  • Raa, B., Dullaert, W., & Van Schaeren, R. (2011). An enriched model for the integrated berth allocation and quay crane assignment problem. Expert Systems with Applications, 38, 14136–14147.

    Google Scholar 

  • Rahman, H. F., & Nielsen, I. (2019). Scheduling automated transport vehicles for material distribution systems. Applied Soft Computing, 82, 105552.

    Google Scholar 

  • Ramirez-Nafarrate, A., Gonzalez-Ramirez, R. G., Smith, N. R., Guerra-Olivares, R., & Voss, S. (2017). Impact on yard efficiency of a truck appointment system for a port terminal. Annals of Operations Research, 258(2), 195–216.

    MathSciNet  Google Scholar 

  • Robenek, T., Umang, N., Bierlaire, M., & Ropke, S. (2014). A branch-and-price algorithm to solve the integrated berth allocation and yard assignment problem in bulk ports. European Journal of Operational Research, 235(2), 399–411.

    MathSciNet  Google Scholar 

  • Salhi, A., Alsoufi, G., & Yang, X. (2019). An evolutionary approach to a combined mixed integer programming model of seaside operations as arise in container ports. Annals of Operations Research, 272(1–2), 69–98.

    MathSciNet  PubMed  Google Scholar 

  • Salido, M. A., Rodriguez-Molins, M., & Barber, F. (2011). Integrated intelligent techniques for remarshaling and berthing in maritime terminals. Advanced Engineering Informatics, 25(3), 435–451.

    Google Scholar 

  • Schulte, F., Lalla-Ruiz, E., González-Ramírez, R. G., & Voß, S. (2017). Reducing port-related empty truck emissions: A mathematical approach for truck appointments with collaboration. Transportation Research Part E: Logistics and Transportation Review, 105, 195–212.

    Google Scholar 

  • Shang, X. T., Cao, J. X., & Ren, J. (2016). A robust optimization approach to the integrated berth allocation and quay crane assignment problem. Transportation Research Part E-Logistics and Transportation Review, 94, 44–65.

    Google Scholar 

  • Shouwen, J., Di, L., Zhengrong, C., & Dong, G. (2021). Integrated scheduling in automated container terminals considering AGV conflict-free routing. Transportation Letters, 13(7), 501–513.

    Google Scholar 

  • Sim, J. (2018). A carbon emission evaluation model for a container terminal. Journal of Cleaner Production, 186, 526–533.

    CAS  Google Scholar 

  • Tang, L., Zhao, J., & Liu, J. (2014). Modeling and solution of the joint quay crane and truck scheduling problem. European Journal of Operational Research, 236(3), 978–990.

    MathSciNet  Google Scholar 

  • Tan, C., & He, J. (2016). Integrated yard space allocation and yard crane deployment problem in resource-limited container terminals. Scientific Programming, 1–12, 2016.

    Google Scholar 

  • Tan, C., & He, J. (2021). Integrated proactive and reactive strategies for sustainable berth allocation and quay crane assignment under uncertainty. Annals of Operations Research. https://doi.org/10.1007/s10479-020-03891-3

    Article  PubMed  PubMed Central  Google Scholar 

  • Tasoglu, G., & Yildiz, G. (2019). Simulated annealing based simulation optimization method for solving integrated berth allocation and quay crane scheduling problems. Simulation Modelling Practice And Theory, 97, 1–29.

    Google Scholar 

  • Torkjazi, M., Huynh, N., & Shiri, S. (2018). Truck appointment systems considering impact to drayage truck tours. Transportation Research Part E-Logistics And Transportation Review, 116, 208–228.

    Google Scholar 

  • Turkogullari, Y. B., Caner Taskin, Z., Aras, N., & Kuban Altinel, I. (2016). Optimal berth allocation, time-variant quay crane assignment and scheduling with crane setups in container terminals. European Journal of Operational Research, 254(3), 985–1001.

    MathSciNet  Google Scholar 

  • Umang, N., Bierlaire, M., & Erera, A. L. (2017). Real-time management of berth allocation with stochastic arrival and handling times. Journal of Scheduling, 20(1), 67–83.

    MathSciNet  Google Scholar 

  • United Nations Environment Programme.(2021). The heat is on emissions gap report 2021. UNEP: Technical report.

  • Vacca, I., Salani, M., & Bierlaire, M. (2013). An exact algorithm for the integrated planning of berth allocation and quay crane assignment. Transportation Science, 47(2), 148–161.

    Google Scholar 

  • Vandani, B., Mansour, F., Soltani, M., & Veysmoradi, D. (2019). Bi-objective optimization for integrating quay crane and internal truck assignment with challenges of trucks sharing. Knowledge-Based Systems, 163, 675–692.

    Google Scholar 

  • Wang, S. (2015). Optimal sequence of container ships in a string. European Journal of Operational Research, 246(3), 850–857.

    MathSciNet  Google Scholar 

  • Wang, Z., & Guo, C. (2018). Minimizing the risk of seaport operations efficiency reduction affected by vessel arrival delay. Industrial Management & Data Systems, 118(7), 1498–1509.

    Google Scholar 

  • Wang, Y., Jiang, X., Lee, L. H., Chew, E. P., & Tan, K. C. (2017). Tree based searching approaches for integrated vehicle dispatching and container allocation in a transshipment hub. Expert Systems with Applications, 74, 139–150.

    Google Scholar 

  • Wang, Y., Xiao, Z., Huang, Y., Hao, Y., & Tianyi, G. (2017). Study of continuous berth allocation algorithm based on fairness maximization. Journal of Engineering Science and Technology Review, 10(5), 116–127.

    Google Scholar 

  • Wang, W., Xinglu, X., Peng, Y., Zhou, Y., & Jiang, Y. (2020). Integrated scheduling of port-centric supply chain: A special focus on the seaborne uncertainties. Journal of Cleaner Production, 262, 1–13.

    Google Scholar 

  • Wang, W., Zhou, Y., Song, X., Tang, G., & Fang, Z. (2017). Operational impact estimation of container inspections at Dalian port: The application of simulation. Simulation, 93(2), 135–148.

    Google Scholar 

  • Wasesa, M., Stam, A., & van Heck, E. (2017). The seaport service rate prediction system: Using drayage truck trajectory data to predict seaport service rates. Decision Support Systems, 95, 37–48.

    Google Scholar 

  • Xiang, X., Liu, C., & Miao, L. (2017). A bi-objective robust model for berth allocation scheduling under uncertainty. Transportation Research Part E-Logistics and Transportation Review, 106, 294–319.

    Google Scholar 

  • Xin, J., Negenborn, R. R., Corman, F., & Lodewijks, G. (2015). Control of interacting machines in automated container terminals using a sequential planning approach for collision avoidance. Transportation Research Part C-Emerging Technologies, 60, 377–396.

    Google Scholar 

  • Yang, Y.-C. (2017). Operating strategies of co2 reduction for a container terminal based on carbon footprint perspective. Journal of Cleaner Production, 141, 472–480.

    CAS  Google Scholar 

  • Yang, Q., Chen, Z., & Yang, H. (2021). A coscheduling model of automated single-beam cranes and AGVs in assembly workshop. Arabian Journal for Science and Engineering, 46(3), 2815–2831.

    Google Scholar 

  • Yang, Y., Zhong, M., Dessouky, Y., & Postolache, O. (2018). An integrated scheduling method for AGV routing in automated container terminals. Computers & Industrial Engineering, 126, 482–493.

    Google Scholar 

  • Yang, Y. J., Zhu, X. N., & Haghani, A. (2019). Multiple equipment integrated scheduling and storage space allocation in rail-water intermodal container terminals considering energy efficiency. Transportation Research Record, 2673(3), 199–209.

    Google Scholar 

  • Yan, B., Zhu, X., Wang, L., & Chang, Y. (2018). Integrated scheduling of rail-mounted gantry cranes, internal trucks and reach stackers in railway operation area of container terminal. Transportation Research Record, 2672(9), 47–58.

    Google Scholar 

  • Yiqin, L., & Le, M. (2014). The integrated optimization of container terminal scheduling with uncertain factors. Computers & Industrial Engineering, 75(1), 209–216.

    Google Scholar 

  • Yu, K., & Yang, J. C. (2019). Milp model and a rolling horizon algorithm for crane scheduling in a hybrid storage container terminal. Mathematical Problems in Engineering, 2019, 1–16.

    Google Scholar 

  • Zehendner, E., & Feillet, D. (2014). Benefits of a truck appointment system on the service quality of inland transport modes at a multimodal container terminal. European Journal of Operational Research, 235(2), 461–469.

    MathSciNet  Google Scholar 

  • Zhang, Q., Hu, W., Duan, J., & Qin, J. (2021). Cooperative scheduling of AGV and ASC in automation container terminal relay operation mode. Mathematical Problems in Engineering, 2021, 1–18.

    Google Scholar 

  • Zhang, Z., & Lee, C.-Y. (2016). Multiobjective approaches for the ship stowage planning problem considering ship stability and container rehandles. IEEE Transactions on Systems Man Cybernetics-Systems, 46(10), 1374–1389.

    Google Scholar 

  • Zhang, X., Zeng, Q., & Yang, Z. (2019). Optimization of truck appointments in container terminals. Maritime Economics & Logistics, 21(1), 125–145.

    Google Scholar 

  • Zheng, F. F., Li, Y., Chu, F., Liu, M., & Xu, Y. F. (2019). Integrated berth allocation and quay crane assignment with maintenance activities. International Journal Of Production Research, 57(11), 3478–3503.

    Google Scholar 

  • Zhen, L., Liang, Z., Zhuge, D., Lee, L. H., & Chew, E. P. (2017). Daily berth planning in a tidal port with channel flow control. Transportation Research Part B-Methodological, 106, 193–217.

    Google Scholar 

  • Zhen, L., Shucheng, Yu., Wang, S., & Sun, Z. (2019). Scheduling quay cranes and yard trucks for unloading operations in container ports. Annals Of Operations Research, 273(1–2), 455–478.

    MathSciNet  Google Scholar 

  • Zhen, L., Yu, S. C., Wang, S. A., & Sun, Z. (2016). Scheduling quay cranes and yard trucks for unloading operations in container ports. Annals Of Operations Research, 273(1–2), 455–478.

    MathSciNet  Google Scholar 

  • Zhong, H., Ziwei, H., & Yip, T. L. (2019). Carbon emissions reduction in china’s container terminals: Optimal strategy formulation and the influence of carbon emissions trading. Journal of Cleaner Production, 219, 518–530.

    Google Scholar 

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Acknowledgements

This work was supported by [Science and Technology Commission of Shanghai Municipality] (Granted numbers [20zd120300] and [18510745100]). The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Authors and Affiliations

  1. Institute of Logistics Science and Engineering, Shanghai Maritime University, 1550 Haigang Ave, Shanghai, 201306, People’s Republic of China

    Fang Yu, Haiqing Yao & Yongsheng Yang

  2. School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, 210003, People’s Republic of China

    Chun Zhang

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  1. Fang Yu
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  2. Chun Zhang
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  3. Haiqing Yao
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  4. Yongsheng Yang
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Correspondence to Fang Yu.

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Yu, F., Zhang, C., Yao, H. et al. Coordinated scheduling problems for sustainable production of container terminals: a literature review. Ann Oper Res 332, 1013–1034 (2024). https://doi.org/10.1007/s10479-023-05676-w

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