Hybrid Estimation of Distribution Algorithm for the Quay Crane Scheduling Problem

The competitiveness of a container terminal is highly conditioned by the time that container vessels spend on it. The proper scheduling of the quay cranes can reduce this time and allows a container terminal to be more attractive to shipping companies. The goal of the Quay Crane Scheduling Problem (QCSP) is to minimize the handling time of the available quay cranes when performing the tasks of loading and unloading containers onto/from a container vessel. This paper proposes a hybrid Estimation of Distribution Algorithm with local search to solve the QCSP. This approach includes a priori knowledge about the problem in the initialization step to reach promising regions of the search space as well as a novel restarting strategy with the aim of avoiding the premature convergence of the search. Furthermore, an approximate evaluation scheme is applied in order to reduce the computational burden. Moreover, its performance is statistically compared with the best optimization method from the literature. Numerical testing results demonstrate the high robustness and efficiency of the developed technique. Additionally, some relevant components of the scheme are individually analyzed to check their effectiveness.

• Development of a hybrid algorithm that combines an Estimation of Distribution Algorithm with local search to solve the Quay Crane Scheduling Problem.
• The proposed algorithm significantly reduces the computational time required by other algorithms from the related literature while reaching high-quality solutions.
• The efficiency of the proposed algorithm supposes an important contribution to the management of container vessels arriving to maritime container terminals and, therefore, let tackle more general approaches where different logistical problems are integrated.
• The integration of problems that appear in a container terminal will eventually let develop an intelligent system applicable to real situations.