Yard Crane Scheduling Between Blocks Of Container Terminals

Yard crane as a container terminal yard handling machinery, the reasonableness of its dispatching will directly affect the efficiency of container terminal’s operations, but also affects the reputation of the port, and embodies the marina management level and in overall competitiveness among peers. The field in the container yard crane scheduling process, the container terminal is responsible for scheduling staff would normally based on experience for each container area is allocated a certain number of block in order to bridge the appropriate loading and unloading work as soon as possible so that his ship can be fully guaranteed, enhance customer satisfaction. However, the efficiency in loading and unloading ships, while the allocation of resources yard crane did not consider it reasonable intervals and each yard cranes collaborative scheduling problems are generally ignored. Scheduling for the lack of these will make wasting the resources, increased traffic congestion within the yard. These circumstances increase the container terminal’s costs, reduce the safety factor, leading to dock benefits reduced. Therefore, for each block the yard crane scheduling is necessary.In order to solve this yard crane unreasonable allocation and scheduling a series of negative effects brought about by the proposed rolling-plan based yard crane scheduling policy. Gives a definition of a rolling plan, combined with scheduling problems rolling plan elaborated strategy application methods. Consider the many practical constraints and the configuration of the bridge as a variable field to optimize the establishment of a task to delay the amount of the total field transitions bridge time and total idle time minimizing the objective function of the three scheduling model. Combined with model characteristics and scale of the problem, this article uses heuristic algorithm and genetic algorithm optimization combining problem solving. Which heuristic algorithm is used to ensure that the resulting initial solutions are feasible solution, and then narrow the search space of genetic algorithm. Genetic algorithms are used for deep optimization, after several iterations come to a reasonable initial field distribution and crane scheduling strategy. Finally, a numerical example of the constructed model and the effectiveness of the algorithm, but also summed up the lack of research and work towards the future, but on the whole this study was able to provide a reference for yard crane scheduling problems in container terminals.