K.Azaryoun - Master Degree Student of Iran University of Science and Technology and IT expert of Tidewater Company
M.Analoui - Professor of Iran University of Science and Technology, Computer Department.
K.Jalali - IT Manager of Tidewater Company, Professor of Islamic Azad University

There are three significant bottlenecks at Shahid Rajee port complex as the largest Iranian container terminal as well as other eminent container terminals in the world: load and unload scheduling, resource management and yard allocation. These bottlenecks are correlated to each other. Since an impertinent yard allocation will hinder resource management and load and unload scheduling systems to attain to a perfect result so obviously it should be regarded as a chief problem in container terminals. Classifiers are abstract entities which try to label unknown objects from a specified dataset. Each classifier works based on its own accuracy, so sometimes it is preferable to use a collection of classifiers (which is called ensemble) instead of single ones and aggregate the answers of each classifier to obtain the final result. Majority Vote is the most famous approach in this case. In this article we have extended combining classifiers and introduced a new genetic approach for the aggregation phase. As a matter of fact in this article a methodology based on the concept of genetic algorithms (GA) is developed for combining classifiers systems to solve yard allocation problem, on the other hand, we have proposed a genetic based approach for fusion classification to be used as a core of yard management system. Both chief attitudes of genetic algorithms, exploration and exploitation, have been used in order to find the most appropriate label for each dataset member upon the probability for each classifier in the ensemble to give the correct class label of each class. The superiority of the proposed system against some customary approaches has been presented for some real data of Shahid Rajaee port complex.

Yard Allocation System, Combining Classifier Systems, Container Terminal, Fusion Classifiers, Genetic Algorithms, Majority Vote