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Automation of handling and storage of containers at Ports by using Ant Colony Optimization Algorithm

عنوان مقاله: Automation of handling and storage of containers at Ports by using Ant Colony Optimization Algorithm
شناسه ملی مقاله: ICOPMAS06_110
منتشر شده در ششمین همایش بین المللی سواحل، بنادر و سازه های دریایی در سال 1383
مشخصات نویسندگان مقاله:

Hamid Javadi - Rector of Institute
Kambiz Alempour - Chief Designer
Ali Dehghanian - Expert of Hydro-aerostatic

خلاصه مقاله:
Transportation of goods using containers is rapidly growing.Future planning of container terminals requires new control system for optimazation .Experience shows that the most critical constraint on container terminal is capacity and ship loading and unloading time.By using Ant Colony Control Algorithm(ACCA) finding the optimized path for container in a large port and time reduction would be a advanced automated solution[1] . Real ants are capable of finding the shortest path from a food source to the nest without using visual cues(fig 1) Also, they are capable of adapting to changes in the environment, for example finding a new shortest path once the old one is no longer feasible due to a new obstacle. Ants are moving on a straight line that connects a food source to their nest. It is well known that the primary means for ants to form and maintain the line is a pheromone trail. Ants deposit a certain amount of pheromone while walking, and each ant probabilistically prefers to follow a direction rich in pheromone[2]. This elementary behavior of real ants can be used to explain how they can find the shortest path that reconnects a broken line after the sudden appearance of an unexpected obstacle has interrupted the initial path. In fact, once the obstacle has appeared, those ants which are just in front of the obstacle cannot continue to follow the pheromone trail and therefore they have to choose between turning right or left. In this situation we can expect half the ants to choose to turn right and the other half to turn left. A very similar situation can be found on the other side of the obstacle[3] . This research introduces a new search methodology based on a advanced algorithm and its application to the solution of a classical optimization problem for automation of handling and storage of containers at ports (fig 2). In this research was shown that speed of the storage and retrieval of the containers would be higher than the traditional method by using ant colony method.

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/3309/