A Coevolutionary Algorithm for Balancing and Sequencing in Mixed Model Assembly Lines

Authors:
Yeo Keun Kim;Jae Yun Kim;Yeongho Kim
Affiliations:
Department of Industrial Engineering, Chonnam National University, 300 yongbongdong, Pukku, Kwangju 500-757, Republic of Korea. kimyk@chonnam.chonnam.ac.kr;Department of Industrial Engineering, Chonnam National University, 300 yongbongdong, Pukku, Kwangju 500-757, Republic of Korea. kimjy@chonnam.chonnam.ac.kr;Department of Industrial Engineering, Seoul National University, Seoul 151-742, Republic of Korea. ykim@cybernet.snu.ac.kr
Venue:
Applied Intelligence
Year:
2000

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Abstract

A mixed model assembly line is a production line where a variety of product models are produced. Line balancing and model sequencing problems are important for an efficient use of such lines. Although the two problems are tightly interrelated with each other, prior researches have considered them separately or sequentially. This paper presents a new method using a coevolutionary algorithm that can solve the two problems at the same time. In the algorithm, it is important to promote population diversity and search efficiency. We adopt a localized interaction within and between populations, and develop methods of selecting symbiotic partners 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. Also presented are the experimental results that demonstrate the proposed algorithm is superior to existing approaches.