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Dynamic Production Scheduling Modeling and Multi-objective Optimization for Automobile Mixed-Model Production

  • Zhenyu Shen
  • Qian Tang
  • Tao HuangEmail author
  • Tianyu Xiong
  • Henry Y. K. Hu
  • Yi Li
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 924)

Abstract

Due to inventory redundancy problem caused by automakers mixed-model production mode, a practical scheduling modeling and multi-objective optimization strategy is presented to increase production and inventory efficiency in this paper. Numerous factors including the general assembly shop, the painting shop, and linear buffer between two workshops have been considered, and a novel dynamic production scheduling model is proposed to achieve three optimization goals: (i) equalize parts consumption rate in the general assembly shop so changes in parts inventory can be predicted; (ii) reduce color switching frequency in the painting shop’s production queue; (iii) reduce waiting time in car body’s buffer zone. Based on this model, an embedded heuristic algorithm with NSGA-2 (No-domination Sorting Genetic Algorithms-II) is employed to solve multi-objective optimization problem. Simulations are finally conducted, when compared with a traditional algorithm, the results are obviously better than traditional algorithm, which validate effectiveness of the proposed model and optimization algorithm.

Keywords

Shop scheduling Inventory control Multi-objective optimization Genetic algorithm 

References

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Zhenyu Shen
    • 1
  • Qian Tang
    • 1
  • Tao Huang
    • 1
    Email author
  • Tianyu Xiong
    • 1
  • Henry Y. K. Hu
    • 1
  • Yi Li
    • 1
  1. 1.State Key Laboratory of Mechanical TransmissionsChongqing UniversityChongqingChina

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