| dc.description.abstract | The merchant shipping perform a fundamental role in the economy of a nation, by linking production to consumption. In shipping expansion scenario, the use of containers for cargo organizing provides greater facility, safety and velocity, thus increasing the productivity of terminals and ships. However, the use of container ships has handling and stability limitations that affect the operating cost of a port terminal. As the cranes can only access the container stacks from the top, carrying out unnecessary removals of blocking containers generates an additional cost of handling and time in loading and unloading operations. Thus, it is necessary to elaborate an efficient stowage plan for loading and unloading operations, minimizing both the shifting and the instability of the vessel. This study proposes an hybrid approach developed by the combination of Genetic Algorithms and Tabu Search metaheuristics, using a rules-based encoding for solution representation, in order to create a computational tool that manage both the rehandling and instability, which are conflicting. In the experiments, pure metaheuristics were compared to the hybrid algorithm and the results demonstrate that the hybridization presents greater efficiency than the pure metaheuristics. The different rules configuration have proven that the proposal of a greater number of rules, in addition to those proposed in the literature, implies better results. The application of a multiple objectives approach has proven the importance of considering the handling and stability in the stowage plan. With the results, it was showed that the use of the proposed approach produces better solutions than those found in the literature. | en |
