International Journal of Industrial Engineering Computations (Jan 2023)

Mixed-model assembly line balancing problem in multi-demand scenarios

  • Kang Wang,
  • Qianqian Han,
  • Zhenping Li

DOI
https://doi.org/10.5267/j.ijiec.2023.9.002
Journal volume & issue
Vol. 14, no. 4
pp. 645 – 658

Abstract

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The mixed-model assembly line balancing problem (MMALBP) in multi-demand scenarios is investigated, which addresses demand fluctuations for each product in each scenario. The objective is to minimize the sum of costs associated with tasks allocation, workstation activation, and penalty costs for unbalanced workloads. A mixed integer programming model is developed to consider the constraint of workstation space capacity. A phased heuristic algorithm is designed to solve the problem. The computational results show that considering demand fluctuations in multiple demand scenarios leads to more balanced workstation loads and improved assembly line production efficiency. Finally, sensitivity analysis of important parameters is conducted to summarize the impact of parameter changes on the results and provide practical management insights.