Study On The Collaborative Scheduling Of Berth And Quay Cranes Under Uncertainty

As an important node of international logistics, container terminal is a typicaldiscrete, stochastic and dynamic large-scale system. The complexity inside the systemand the uncertainty outside the system brings great challenges to the planning andscheduling of container terminals. In the face of these challenges, the academiccommunity has done a lot of related research. In the case of terminal operators, it isnecessary to do terminal planning at the strategic level and terminal scheduling at theoperational level. The former includes long-term decisions such as equipment purchases,while the latter mainly concerns the allocation of berths, quay cranes and many otherresources. Because it involves real-time performances and many other characteristics,scheduling problem in general is much more complex than planning problem, and it hasbecome the focus and frontier of academic research. Many scholars have studied theproblem of berth allocation and quay crane scheduling, who have achieved aconsiderable amount of research results. Some researches focus on model innovation,while others focus on innovation of algorithms. And both mathematical optimizationand simulation technology are used to solve problems in related papers.Berths and quay cranes are known as the two most important resources in containerterminals during loading and unloading operations，the efficient utilization of which hasa great impact on the performance, the competitiveness and even the survival ofcontainer terminals. In recent years, as the awareness about the problem constantlydeepens, and the related theory and technology continues to mature, more and morescholars are focusing on the collaborative scheduling of berths and quay cranes. Thispaper also studies the berth allocation problem (BAP) and quay crane schedulingproblem (QCSP) in an integrated way. We focus on how to develop a robust and costeffective schedule proactively with uncertainties of vessels’arrival times. The berth is ofcontinuous type and coverage ranges of quay cranes are taken into consideration. Amixed integer programming model is constructed, and a heuristic based on geneticalgorithm is applied to solving the problem in large scale. Numerical experiments areconducted to validate the effectiveness and efficiency of the proposed model.On the basis of existing studies, this paper contains the following innovations. The article considers the collaborative scheduling of continuous berth and quay cranes underuncertainty, taking the coverage ranges of quay cranes into consideration. While theexisting researches focus on discrete berth allocation strategy or ignore the schedulingof quay cranes. Besides, a large-scale heuristic combining simple genetic algorithm,gene adjusting heuristic and local optimization heuristic is used to solve themathematical model. Numerical experiments show that the model and heuristic workwell, which successfully balance the cost and robustness of the schedule.