Sequencing Mixed-Model Assembly Lines with Limited Intermediate Buffers by a GA/SA-Based Algorithm

  • Binggang Wang
  • Yunqing Rao
  • Xinyu Shao
  • Mengchang Wang
Part of the Communications in Computer and Information Science book series (CCIS, volume 15)


This study is concerned about how to optimize the input sequence of product models in Mixed-Model Assembly Lines (MMALs) with limited intermediate buffers.Two objectives are considered simultaneously: minimizing the variation in parts usage and minimizing the makespan. The mathematical model is presented by incorporating the two objectives according to their relative importance weights. A hybrid algorithm (GASA), based on a genetic algorithm (GA) and a simulated annealing algorithm (SA), is proposed for solving the model. The performance of the GASA is compared with the GA over various test problems. The results show that, in terms of solutions’ quality, both the GASA and GA can find the same best solution for small-sized problems and the GASA performs better than the GA for mediate and large-sized problems. Moreover, the impact of buffer size on MMAL’s performance is investigated.


Mixed-model assembly lines Limited intermediate buffers  Sequencing GA/SA-based algorithms Genetic algorithms 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Binggang Wang
    • 1
  • Yunqing Rao
    • 1
  • Xinyu Shao
    • 1
  • Mengchang Wang
    • 1
  1. 1.The State Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhanChina

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