Application of genetic optimization algorithm to the crane problem in the shipbuilding industry

In various contexts of the shipbuilding industry as well as in the marine transportation industry, the relocation of objects such as steel plates, containers, etc. by using cranes is a common task. In these operations, crane operators are faced with the problem of starting with a given distribution of objects and restacking them in order to achieve a desired distribution using the least possible effort or movement of the crane. This type of problem involves a practically infinite number of solutions, since the possible combinations of operational order are so numerous. Therefore, it is difficult for the operator to determine the optimal sequence from the candidate processes, and it also is difficult to present a general method that can solve this problem with high degrees of efficiency and reliability. As a result, in practical situations the crane operators on site usually decide the sequence according to their experience and intuition. However, sometimes the planning of the crane operation process is very troublesome and time consuming and is thought to be not necessarily suitable for human beings.In this study we apply a genetic algorithm (GA) that excels at finding solutions to combinatory problems. The sequence of a crane's operation is represented in string expression and with the merit of a population search (i.e., a simultaneous multi-point search) of the GA, excellent operations were efficiently obtained for the practical examples shown in the paper.