Hassan Rashidi - Faculty of Statistics, Mathematics and Computer Science, Allameh Tabataba’i University
Fatemeh Habibi Ehsaee - Faculty of Statistics, Mathematics and Computer Science, Allameh Tabataba’i University
Fereshteh Azadi Parand - Faculty of Statistics, Mathematics and Computer Science, Allameh Tabataba’i University

The efficiency of ports and container terminals is strongly related to the process of loading containers onto and unloading containers from the docked ships. In this research, an issue of integrated equipment management in automated container terminals with the aim of increasing efficiency has been studied. Due to this issue falls into NP-Hard problems, it was divided into two sub-problems: Allocating resources to containers and arranging the containers serviced by automated guided vehicles. Both sub-problems were formulated and expressed using the linear integer-programming model. The first sub-problem is solved by the allocation of random process resources with uniform distribution and the second part is solved using a Sorting Genetic Algorithm. The main parameters of the proposed solution methods were determined with Minitab software and Taguchi techniques. In order to evaluate the efficiency and effectiveness of the proposed solution methods, many numerical experiments have been examined and evaluated. The experimental results show that the proposed solutions are efficient for estimating the service time and the number of automated guided vehicles required to transporting the containers in the container ports.

Automated Container Terminal, Automated Guided Vehicle, Quay, Crane, Yard Crane