Though many methods are applied to solve the combinatorial optimization problem, there are many cases in which the solution cannot be solved in practical computation time, even if the computer becomes more advanced. Recently the "ant colony optimization method (ACO)" has been proposed as one of the meta-heuristic method. This research tried the ACO in ship production field. Firstly, the ACO was applied and verified for the traveling salesman problem (TSP) to obtain the shortest path in many cities, as a representative combinatorial optimization problem. Next, based on the result, the ACO was applied to the problem in search of the optimum torch movement of a welding robot for the assembly of ship hull structure, and of a NC plasma cutting machine of steel plate. As a result, it was confirmed that the ACO is effective to solve the optimum path of machines.

Keywords:
machine learning, shipbuilding, pheromone, optimization problem, Ant, city number, Artificial Intelligence, TSP, end point, application
Subjects:
Artificial intelligence, Information Management and Systems
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2009. The Society of Naval Architects and Marine Engineers
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