¹ SOIE: Laboratoire de Stratégies d’Optimisation et Informatique intelligente
Institut Supérieur de Gestion de Tunis,
41, Rue de la Liberté, Cité Bouchoucha 2000 Le Bardo, Tunis –Tunisie
radhia.zaghdoud@fsg.rnu.tn, k_zidi@ut.edu.sa, khaled.ghedira@isg.rnu.tn
² LAGIS: Laboratoire d’Automatique, Génie Informatique et Signal Ecole Centrale de Lillle, Cité scientifique –
B.P. 48-59651 Villeneuve d’Ascq, Lille-France
khaled.mesghouni@ec-lille.fr

Abstract: The handling operations performed in ports require the use of equipment operating in a dynamic environment. Some tasks may not be fully carried out due to equipment failure or power breakdown that may occur particularly with the automated guided vehicles (AGV). The unavailability of equipment such as AGV has important consequences in terms of respecting the deadlines of different operations that a port should perform, such as the loading and unloading operations of ships. This situation can aggravate if there are also traffic problems in the port with some inaccessible network nodes. A part of the equipment will be blocked or the operations will take longer than expected if they don`t take the optimal path to connect the loading/unloading points and storage areas. These reasons confirm the usefulness of establishing a robust system able to resolve the problem of assigning containers in the static and dynamic environments. In a previous work, we developed a system for assigning containers in a static environment. In order to improve this method, we devote this paper to the study of the robustness of our system to the dynamic environment of the port. The numerical tests included in this paper show an adequate performance of our method for this particular dynamic environment.

Keywords: Assignment, Dynamic, AGV, Containers, Optimization, Genetic Algorithm.

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CITE THIS PAPER AS:
Radhia ZAGHDOUD, Khaled MESGHOUNI, Simon Collart DUTILLEUL, Kamel ZIDI, Khaled GHEDIRA, A Hybrid Method for Assigning Containers to AGVs in the Dynamic Environment of Container Terminals, Studies in Informatics and Control, ISSN 1220-1766, vol. 24 (1), pp. 43-50, 2015. https://doi.org/10.24846/v24i1y201505

1. Introduction

The maritime transportation has a great importance in global manufacturing and international business not only because it‘s the cheapest transportation way, but also because it has a capacity to transport a huge volume of goods. Since the 1960s, with the appearance of containerization, this field has received an important development. It increases the goods transportation speed and the goods volume. As a result of this development, a new container terminal model was erase built and the existing ones were extended. In the Hong Kong terminal container, turnover has been raised from 9 million twenty feet Equivalent Units (TEU) in 1993 to 19 million TEU in 2002[1]. The number of TEUs in Singapore, as the second port around the world, has been doubled, increasing from 9 million to 18 million TEUs [2].

But the seaports sizes increase has a negative effect on ship loading and unloading operations rapidity because it makes it very slow. As a consequence, the ship has to wait for a longer time at the port. Facing the challenge of the big increase of the container’s number, the transportation systems of container terminals have to minimize the loading and unloading operation duration.In order to perform this operation, the researchers in this field have to decompose it in some subproblems such as storage containers problem, scheduling AGVs and quay cranes problems. Due to the big number of equipements, the environment in the container terminal is uncertain and complexe. All the operations are integrated, so each operation depends on several constraints.