A mathematical model and a genetic algorithm for two-sided assembly line balancing

  • Authors:
  • Yeo Keun Kim;Won Seop Song;Jun Hyuk Kim

  • Affiliations:
  • Department of Industrial Engineering, Chonnam National University, Gwangju 500-757, Republic of Korea;Department of Industrial Engineering, Chonnam National University, Gwangju 500-757, Republic of Korea;Department of Industrial Engineering, Chonnam National University, Gwangju 500-757, Republic of Korea

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2009

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Abstract

A two-sided assembly line is a type of production line where tasks are performed in parallel at both sides of the line. The line is often found in producing large products such as trucks and buses. This paper presents a mathematical model and a genetic algorithm (GA) for two-sided assembly line balancing (two-ALB). The mathematical model can be used as a foundation for further practical development in the design of two-sided assembly lines. In the GA, we adopt the strategy of localized evolution and steady-state reproduction to promote population diversity and search efficiency. When designing the GA components, including encoding and decoding schemes, procedures of forming the initial population, and genetic operators, we take account of the features specific to two-ALB. Through computational experiments, the performance of the proposed GA is compared with that of a heuristic and an existing GA with various problem instances. The experimental results show that the proposed GA outperforms the heuristic and the compared GA.