Simulation and genetic algorithms for ship planning and shipyard layout

The goal of our research is to develop a collection of software tools to be integrated into the existing industrial software environment to support terminal operators in making strategic decisions about resource allocation and terminal organization. We believe that the first important step in this process is to define a simulation tool to plan and optimize the placement of containers in the terminal. The decision about where a container is to be placed in the terminal yard depends on many parameters: the present occupancy level of the container area (or cluster), the final destination of the containers, the best position to dock the ship, the container's size, the container's content and so on. The problem is difficult because of the competing nature of these parameters and because the containers arrive some weeks before the ship's actual arrival date. In this paper, we describe the use of genetic algorithms (GAs) to perform two tasks: planning (or scheduling) the cluster creation and optimally locating the clusters in the yard. We discuss each GA in detail and present preliminary results.