On Optimization Of Resource Schedule In Container Terminal Yard

With the development of the economic globalization and gradual improvement of socialism market economy of our country, foreign trade develops very fast, and the thruput increases every year, which puts forward higher requirement to the container terminal management. The terminal yard is a region for transferring, managing, placing and repairing containers in container terminal, and its efficiency would affect the competitiveness of container terminal directly, so it is important to optimize the resource schedule of the container terminal. In the terminal yard, gantry cranes and container trucks are very important resource, and the effective use of them can elevate the operational efficiency of container terminal tremendously.This thesis uses operation research, optimizing theory and computer simulation to analyze and research on the schedule optimization of gantry cranes and path optimization of container trucks. Work in two areas of this thesis is shown as follows:1. Research on the schedule optimization of gantry cranes when there are several tasks and the gantry cranes are insufficient. Ant colony algorithm is used to solve this problem. In the procedure of solving the problem using ant colony algorithm, we design an"ant walking path"strategy for the problem where there are several gantry cranes in the container yard. The simulation data indicates that within an acceptable period of time the result gotten by ant colony algorithm is better than genetic algorithm and tabu search.2. Research on the path optimization of container trucks based on pool strategy. We use IMTS method to solve this problem which combines the advantages of both immune algorithm and tabu search. It is not easy for IMTS to sink into the local best solution, and in the meanwhile, it avoids the disadvantage of tabu search that initial solution has a great impact on the result. With data examples, we analyze the affection of operation queue and pool strategy to the route of container trucks. The result indicates that pool strategy decreases the container trucks'length of route, saves the time of transportation and improves the efficiency of the container trucks.