A memetic algorithm approach for batch-model assembly line balancing problem of sub-block in shipbuilding

Although assembly line balancing problem has been an attractive field of research in many industries over the past decades, few researches focused on the problems in shipbuilding. In this contribution, we deal with a more realistic assembly line for sub-block in shipbuilding, through which lots of small different products were produced. Thus, the problem becomes more complex, which can be regarded as a variant of the classical assembly line balancing problem, batch-model assembly line balancing problem with space and sequence constraints. Our goal is to find the optimal division of the total assignment into different production batches based on the balance of the station workloads and higher efficiencies of the workers and equipments. We solve the said problem with a memetic algorithm, which is illustrated in detail. The validity of the proposed algorithms is tested using the real data of the sub-block assembly in shipbuilding, and the experiment results demonstrate that the proposed algorithm outperforms highly the existing standard genetic algorithm in terms of ability to find the optimal solutions.