Balancing and sequencing mixed-model U-lines with a co-evolutionary algorithm

Abstract

A mixed-model production line is such a line where a variety of product models are produced. In U-lines used in the just-in-time production system, the strategy of mixing product models is often employed to provide various types of products to customers on time. Line balancing and model sequencing problems are important for an efficient use of mixed-model U-lines. Although the two problems are tightly interrelated with each other, prior research has considered them separately or sequentially. In this paper, a new approach using an artificial intelligence search technique, called co-evolutionary algorithm, is proposed to solve the two problems at the same time. To promote population diversity and search efficiency in the algorithm, we adopt strategies of localized evolution and steady-state reproduction, and develop methods of selecting environmental individuals and evaluating fitness. Efficient genetic representations and operator schemes are also provided. When designing the schemes, we take into account the features specific to the problems. The experimental results demonstrate that the proposed algorithm outperforms existing approaches.