Integrated Scheduling Model And Algorithm Study In Container Terminals

With the globalization of trade, the logistics and transportation have got rapid growth. Container transportation, which began in the 1950s, has developed greatly within just several decades for its high efficiency, fast speed and low cost. At the same time, the competitions in different container terminals, especially in those which are located in the same districts, become stronger. For container terminals, the high efficiency is one of the most important facts to gain a competitive advantage. Therefore, research on scheduling problems in container terminals to increase the efficiency is very important and necessary.Based on the literature review and the investigation in Shekou International Container Terminal and Yantian International Container Terminal, this study provides an integrated model for unloaded work scheduling in container terminals. Compared with other models, this model is suitable for container terminals without buffer and considers the integrated scheduling of yard locations, container trucks and yard cranes. The proposed model also considers the different working time of quay cranes and yard cranes for different containers and yard locations, the traffic delay produced by traffic congestion and drivers'operation, and the different roundtrip distances between yard and quayside. These improvements make the model more practical.This study proves the proposed scheduling problem is NP-complete, which means that there exists no polynomial time algorithm for the exact solution. Therefore, this study develops a genetic algorithm to obtain approximate optimal solutions and realizes a program based on Visual C++. Nine random instances with small sizes, nine ones with large sizes and five ones with super large sizes are conducted to evaluate the performance of the proposed model and genetic algorithm. Computational results show that the genetic algorithm is effective and efficient in solving this integrated scheduling problem. Compared with other scheduling methods in container terminals, the genetic algorithm increases the efficiency of unloaded work by 7% for instances with practical sizes.The proposed model and algorithm can be utilized practically in unloaded scheduling, resource allocation and application in other container terminals. The unloaded scheduling can allocate yard locations, container trucks and yard cranes to get a better scheduling with a shorter working time. Resource allocation allocates proper amount of container trucks and yard cranes in order to finish work efficiently and avoid the waste of resource in container terminals. Application in other container terminals means the study can be used in container terminals with buffer. Because of the consideration of yard locations and traffic delay, the study can get a better scheduling compared with other research.