Integrated Berth Allocation and Time-Variant Quay Crane Scheduling with Tidal Impact in Approach Channel

Abstract

This paper addresses the integrated problem of dynamic continuous berth allocation and time-variant quay crane scheduling in container terminals and introduces the factor of tidal impacts into the problem. We mainly consider the impact of tides on the transport capacity of an approach channel that connects quay and anchorage. An integer linear programming model is developed, and then three heuristic algorithms, Genetic Algorithm, Hybrid Particle Swarm Optimization, and Hybrid Simulated Annealing, are proposed to solve the model. Numerical experiments are conducted to verify the efficient performances of the proposed heuristics. Moreover, experimental results also demonstrate the nonignorable impact of tides on the vessel turnaround time and the utilization of berth and quay cranes.

An Efficient Procedure for Inserting Buffers to Generate Robust Berth Plans in Container Terminals

“…e first is the berthing time, or operation starting time s i , which is related to vessel arrival time a i , processing time p i , and required departure time in timetable d i . It should be noted that earlier departure is welcomed by shipping liners because it promotes the flexibility of following voyage [29]. Besides, it is also encouraged by port operators since it releases quay space and cranes for other vessels, which can improve the overall operation efficiency.…”

Collaborative Scheduling Optimization of Container Port Berths and Cranes under Low-Carbon Environment

“…Jiao et al [4] introduced the tidal influence factor, on the basis of which the main consideration is the impact of tides on the transportation capacity of the connecting terminal and the transportation capacity of the inlet channel connecting the wharf and the anchorage. Soroush and Reza et al [5] focused mainly on tidal influences, draft depth limitations, and safe distances in and out of the harbor.…”

Research on Scheduling of Terminal Frontier Resources Based on Multi-Objective Optimization

“…And the research content extends from simple strategies to single resource scheduling and then to joint scheduling of multiple resources. Several scholars have introduced heuristic algorithms into the study of this problem, such as genetic algorithms, simulated annealing algorithms, and particle swarm algorithms [5][6][7][8]. Then the mathematical models have been continuously adapted according to the actual operational scenarios of the terminals.…”