Energy-aware Integrated Scheduling for Container Terminals with Conflict-free AGVs

Zhaolin Zhong , Yiyun Guo , Jihui Zhang , Shengxiang Yang

Journal of Systems Science and Systems Engineering ›› 2023, Vol. 32 ›› Issue (4) : 413 -443.

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Journal of Systems Science and Systems Engineering ›› 2023, Vol. 32 ›› Issue (4) : 413 -443. DOI: 10.1007/s11518-023-5563-y
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Energy-aware Integrated Scheduling for Container Terminals with Conflict-free AGVs

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Abstract

For automated container terminals, the effective integrated scheduling of different kinds of equipment such as quay cranes (QCs), automated guided vehicles (AGVs), and yard cranes (YCs) is of great significance in reducing energy consumption and achieving sustainable development. Aiming at the joint scheduling of AGVs and YCs with consideration of conflict-free path planning for AGVs as well as capacity constraints on AGV-mate which is also called buffer bracket in blocks, a mixed integer programming model is established to minimize the energy consumption of AGVs and YCs for the given loading/unloading task. A solution method based on a novel bi-level genetic algorithm (BGA), in which the outer and the inner layer search the optimal dispatching strategy for QCs and YCs, respectively, is designed. The validity of the model and the algorithm is verified by simulation experiments, which take the Port of Qingdao as an example and the performance under different conflicting resolution strategies is compared. The results show that, for the given task, the proposed solution to conflict-free path and the schedule provided by the algorithm can complete the task with minimum energy consumption without loss of AGVs utilization, and the number of AGV-mates should be adjusted according to the task rather than keeping unchanged. Comparison results indicate that our proposed approach could efficiently find solutions within 6% optimality gaps. Energy consumption is dropped by an average of 15%.

Keywords

Automated container terminal / conflict-free routing / energy saving / improved genetic algorithm

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Zhaolin Zhong, Yiyun Guo, Jihui Zhang, Shengxiang Yang. Energy-aware Integrated Scheduling for Container Terminals with Conflict-free AGVs. Journal of Systems Science and Systems Engineering, 2023, 32(4): 413-443 DOI:10.1007/s11518-023-5563-y

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References

[1]

Alamoush A S, Ballini F, Olcer A I. Ports’ technical and operational measures to reduce greenhouse gas emission and improve energy efficiency: A review. Marine Pollution Bulletin, 2020, 160: 111508.

[2]

Ali A, Al-Bazi A, Palade V. A constrained fuzzy knowledge-based system for the management of container yard operations. International Journal of Fuzzy Systems, 2018, 20(4): 1205-1223.

[3]

Amelie E. A decomposition-based approach to the scheduling of identical automated yard cranes at container terminals. Journal of Scheduling, 2019, 22(5): 517-541.

[4]

Asma O B, Najoua D. Minimizing makespan in a three-stage hybrid flow shop with dedicated machines. International Journal of Industrial Engineering Computations, 2019, 10(2): 161-176.

[5]

Chang Y, Zhu X, Yan B, Wang L. Integrated scheduling of handling operations in railway container terminals. Transportation Letters, 2019, 11(7): 402-412.

[6]

Chen X, He S, Zhang Y, Tong L, Zhou X. Yard crane and AGV scheduling in automated container terminal: A multi-robot task allocation framework. Transportation Research Part C: Emerging Technologies, 2020, 114: 241-271.

[7]

Chu F, Gailus S, Liu L, Ni L. The Future of Automated Ports, 2018, USA: McKinsey & Company

[8]

Du Y Q, Meng Q, Wang S A, Kuang H B. Two-phase optimal solutions for ship speed and trim optimization over a voyage using voyage report data. Transportation Research Part B: Methodological, 2019, 122: 88-114.

[9]

Fan H, Peng W, Ma M, Yue L. Storage space allocation and twin automated stacking cranes scheduling in automated container terminals. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(9): 14336-14348.

[10]

Fazlollahtabar H, Hassanli S. Hybrid cost and time path planning for multiple autonomous guided vehicles. Applied Intelligence, 2018, 48(2): 482-498.

[11]

Fenton C P, Joerss S M, Saxon S, Stone M. Brave New World? Container Transport in 2043, 2018, the Netherlands: TTClub and McKinsey & Company

[12]

Ferry R, Ade S, Bona F R Suprayog Discrete event simulation model for external yard choice of import container terminal in a port buffer area. AIP Conference Proceedings, 2017, 1855: 40014.

[13]

GloMEEP Project, IAPH (2018). Port Emissions Toolkit — Guide No. 2: Development of Port Emissions Reduction Strategies. https://glomeep.imo.org/wp-content/uploads/2018/10/port-emissions-toolkit-g2-online.pdf.

[14]

GREENPORT (2019). Collaborative working key to net zero goals. https://www.greenport.com/news101/energy-and-technology/collaborative-working-key-to-net-zero-goal.

[15]

Grunow M, Günther H O, Lehmann M. Günther H-O, Kim K H. Container terminals and automated transport systems. Container Terminals and Automated Transport Systems, 2005, Germany: Springer.

[16]

He J, Huang Y, Yan W, Wang S. Integrated internal truck, yard crane and quay crane scheduling in a container terminal considering energy consumption. Expert Systems with Applications, 2015, 42(5): 2464-2487.

[17]

Homayouni S M, Motlagh O. A genetic algorithm for optimization of integrated scheduling of cranes, vehicles, and storage platforms at automated container terminals. Journal of Computational and Applied Mathematics, 2014, 270: 545-556.

[18]

Hu H, Chen X, Wang T, Zhang Y. A three-stage decomposition method for the joint vehicle dispatching and storage allocation problem in automated container terminals. Computers & Industrail Engineering, 2019, 129: 90-101.

[19]

Hu Y, Dong L, Xu L. Multi-AGV dispatching and routing problem based on a three-stage decomposition method. Mathematical Biosciences and Engineering, 2020, 17(5): 5150-5172.

[20]

Infiniti Research Limited (2020). Global Automated Container Terminal Market 2020–2024.

[21]

Iris C, Lee Lam J S. A review of energy efficiency in ports: Operational strategies, technologies and energy management systems. Renewable and Sustainable Energy Reviews, 2019, 112: 170-182.

[22]

Ja A H, Cho S W, Pak M S. Fuel consumption within cargo operations at the port industry — A simulation analysis on the case of S Port company in the UK. The Asian Journal of Shipping & Logistics, 2012, 28(2): 227-254.

[23]

Jenny N, Dirk B, Erwin P. Container dispatching and conflict-free yard crane routing in an automated container terminal. Transportation Science, 2018, 52(5): 1059-1076.

[24]

Ji S, Luan D, Chen Z, Guo D. Integrated scheduling in automated container terminals considering AGV conflict-free routing. Transportation Letters, 2020, 13(7): 501-513.

[25]

Jonker T, Duinkerken M B, Yorke-Smith S, de Waal A, Negenborn R R. Coordinated optimization of equipment operations in a container terminal. Flexible Services and Manufacturing Journal, 2021, 33: 281-311.

[26]

Kizilay D, Deniz T E. A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals. Flexible Services and Manufacturing Journal, 2021, 33: 1-42.

[27]

Kizilay D, Eliiyi D T, Van H P. Constraint and mathematical programming models for integrated port container terminal operations. European Journal of Operational Research, 2018, 10848: 344-360.

[28]

Kon W K, Rahman N S F A, Hanafiah R M, Hamid S A. The global trends of automated container terminal: A systematic literature review. Maritime Business Review, 2021, 6(3): 206-233.

[29]

Lee D H, Cao Z, Chen J, Cao J. Load scheduling of multiple yard crane systems in container terminal with buffer areas. Transportation Research Record, 2006, 2097: 70-77.

[30]

Li Y, Chu F, Zheng F, Liu M. A bi-objective optimization for integrated berth allocation and quay crane assignment with preventive maintenance activities. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(4): 2938-2955.

[31]

Martinez M J, Barbara V P, Gimenez M J. Energy efficiency and CO2 emissions of port container terminal equipment: Evidence from the Port of Valencia. Energy Policy, 2019, 131: 312-319.

[32]

Mi C, Huang Y, Fu C, Zhang Z, Postolache O. Vision-based measurement: Actualities and developing trends in automated container terminals. IEEE Instrumentation & Measurement Magazine, 2021, 24(4): 65-76.

[33]

Miyamoto T, Inoue K. Local and random searches for dispatch and conflict free routing problem of capacitated AGV systems. Computers & Industrial Engineering, 2016, 91: 1-9.

[34]

Moller A P (2011). APM terminals to retrofit and electrify RTG fleet worldwide. http://www.apmterminals.com.

[35]

Schmidt J, Barlag C M, Eisel M, Kolbe L M, Appelrath H J. Using battery-electric AGVs in container terminals: Assessing the potential and optimizing the economic viability. Research in Transportation Business & Management, 2015, 17: 99-111.

[36]

Sim J. A carbon emission evaluation model for a container terminal. Journal of Cleaner Production, 2018, 186: 526-533.

[37]

Sirimanne S N, Hoffman J, Juan W, et al. (2019). Review of maritime transport. United Nations Conference on Trade and Development (UNCTAD), Geneva, Switzerland 2019.

[38]

Stahlbock R, Vob S. Operations research at container terminals: a literature update. OR Spectrum, 2008, 30(1): 1-52.

[39]

Steenken D, Vob S, Stahlbock R. Container terminal operation and operations research — A classification and literature review. OR Spectrum, 2004, 26(1): 3-49.

[40]

Tan C, He J, Zhen L (2016). Integrated yard space allocation and yard crane deployment problem in resource-limited container terminals. Scientific Programming: 6421943.

[41]

UNCTAD (2019). Review of maritime transport. United Nations Conference on Trade and Development, New York. Available from: http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=13321.

[42]

Venturini G, Iris C, Kontovas C A, Larsen A. The multi-port berth allocation problem with speed optimization and emission considerations. Transportation Research Part D: Transport and Environment, 2017, 54: 142-159.

[43]

Xin J, Meng C, Ariano A D, Wang D, Negenborn R R. Mixed-integer nonlinear programming for energy-efficient container handling: Formulation and customized genetic algorithm. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(8): 10542-10555.

[44]

Xin J, Negenborn R R, Lodewijks G. Energy-aware control for automated container terminals using integrated flow shop scheduling and optimal control. Transportation Research Part C: Emerging Technologies, 2014, 44: 214-230.

[45]

Yang Y, Zhang X, Wu Z. A simulation study on the automated container storage yard cranes system. Advances in Transdisciplinary Engineering, 2017, 5: 693-700.

[46]

Yang Y, Zhong M, Postolache O. An integrated scheduling method for AGV routing in automated container terminals. Computers & Industrial Engineering, 2018, 126: 482-493.

[47]

Yang Y, Zhu X, Ali H. Multiple Equipment Integrated Scheduling and Storage Space Allocation in Rail-Water Intermodal Container Terminals Considering Energy Efficiency. Transportation Research Record, 2019, 2673(3): 199-209.

[48]

Yue L, Fan H, Zhai C. Joint configuration and scheduling optimization of a dual-trolley quay crane and automatic guided vehicles with consideration of vessel stability. Sustainability, 2019, 12(1): 24.

[49]

Zhan X, Xu L, Li A. Study on AGVs battery charging strategy for improving utilization. Procedia CIRP, 2019, 81: 558-563.

[50]

Zhang C, Wu T, Zheng L, Miao L. A lagrangian relaxation-based algorithm for the allocation of yard activities with different priorities. Journal of Systems Science and Systems Engineering, 2013, 22(2): 227-252.

[51]

Zhang Z, Guo Q, Chen J, et al. Collision-free route planning for multiple AGVs in an automated warehouse based on collision classification. IEEE Access, 2018, 6: 26022-26035.

[52]

Zhang X, Zeng Q, Shen J B. Modeling the productivity and stability of a terminal operation system with quay crane double cycling. Transportation Research Part E: Logistics and Transportation Review, 2019, 122: 181-197.

[53]

Zhang C, Guan H, Yuan Y, Chen W. Machine learning-driven algorithms for the container relocation problem. Transportation Research Part B: Methodological, 2020, 139: 102-131.

[54]

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: 1–18.

[55]

Zhen L, Yu S, Wang S, Sun Z. Scheduling quay cranes and yard trucks for unloading operations in container ports. Annals of Operations Research, 2019, 273(1): 455-478.

[56]

Zhen L, Zhuge D, Murong L W, Yan R, Wang S A (2019b). Operation management of green ports and shipping networks: Overview and research opportunities. Frontiers of Engineering Management: 1–11.

[57]

Zhong M, Yang Y, Zhou Y, Postolache O (2019). Adaptive auto-tuning mathematical approaches for integrated optimization of automated container terminal. Mathematical Problems in Engineering: 7641670.

[58]

Zhong M, Yang Y, Dessouky Y, Postolache O. Multi-AGV scheduling for conflict-free path planning in automated container terminals. Computers & Industrial Engineering, 2020, 142: 106371.

[59]

Zhuang Z L, Zhang Z L, Teng H, Qin W, Fang H J. Optimization for integrated scheduling of intelligent handling equipment with bidirectional flows and limited buffers at automated container terminals. Computers & Operations Research, 2022, 145: 105863.

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