Artificial Intelligence for Automatic Container Stowage Planning Optimisation

The paper explains and compares a range of approaches to the solution of the container-ship stowage problem, which focuses on the reliable production of valid, sub-optimal solutions. These include the strong decomposition of the problem into different conceptual levels of planning to which branch h bound, Tabu search techniques and Genetic algorithms have been applied. A particular focus lies on the relationships between the methods of solution and the corresponding models of cargo and stowage spaces, and the consequences that these models have for the accuracy and usefulness of the solutions produced.