The Crane Scheduling Problem and the Hybrid Intelligent Optimization Algorithm GASA

In the operations of the container ports, quay crane scheduling is critical to the operational efficiency of a container terminal. In this paper we present an improved model for the quay crane scheduling problem and solve this mix integer programming model by the genetic algorithm GA and the hybrid intelligent optimization algorithm GASA respectively. Compared with the genetic algorithm, the hybrid intelligent optimization algorithm GASA increases the diversity of the individuals, accelerates the evolution process and avoids sinking into the local minimal solution.