Hybrid rolling-horizon optimization for berth allocation and quay crane assignment with unscheduled vessels |
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| Affiliation: | 1. State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;2. School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore;3. Department of Mechanical and Electromechanical Engineering, National ILan University, ILan 26041, Taiwan;4. Huazhong University of Science and Technology – Wuxi Research Institute, Wuxi 214000, China;5. School of Mechanical Engineering, Hubei University of Technology, Wuhan 430072, China;1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China;2. School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China;1. School of Traffic & Transportation Engineering, Central South University, Changsha, 410075, China;2. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang, 443002, China;3. College of Electrical Engineering and New Energy, China Three Gorges University, 443002, Yichang, China;4. School of Engineering, Deakin University, Waurn Ponds, Victoria, 3216, Australia;5. School of Hydropower and Information Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China |
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| Abstract: | Port operations usually suffer from uncertainties, such as vessels’ arrival time and handling time and unscheduled vessels. To address this, this study presents a dynamic berth allocation and crane assignment specific problem (BACASP) when unscheduled vessels arrive at the port, which is branded the berth allocation and quay crane assignment specific problem with unscheduled vessels (UBACASP). A rolling-horizon based method is proposed to decompose the UBACASP into a multi-stage static decision BACASP, wherein a rescheduling margin-based hybrid rolling-horizon optimization method is developed by incorporating the event-driven and periodical rolling-horizon strategies as the urgency of dynamic events is evaluated. In each rolling horizon, a mixed integer linear programming model (MILP) is presented for the BACASP to minimize the total port stay time of vessels and the penalties of delays associated with the spatial and temporal constraints, such as the length of continuous berth, number of quay cranes (QCs) and non-crossing of QCs. A discretization strategy is designed to divide the continuous berth into discrete segments, and convert the BACASP to a discrete combinatorial optimization problem, which is efficiently solved by the proposed adaptive large neighborhood search algorithm (ALNS). Case studies with different problem characteristics are conducted to prove the effectiveness of the solution methods proposed in this study. Moreover, the performances of the ALNS and the existing methods for solving the BACASP are compared, and the advantages and disadvantages of different rolling strategies under different degrees of uncertainties are deeply analyzed. |
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| Keywords: | Berth allocation and quay crane assignment Adaptive large neighborhood search Rolling-horizon optimization Discretization strategy Heuristic method |
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