• DocumentCode
    3044471
  • Title

    A Novel Two-Level Genetic Algorithm for Integrated Process Planning and Scheduling

  • Author

    Liang Wan ; Xinyu Li ; Liang Gao ; Xiaoyu Wen ; Wenwen Wang

  • Author_Institution
    State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    2790
  • Lastpage
    2795
  • Abstract
    Process planning and scheduling are two important sub-systems in modern manufacturing system. In manufacturing system, the two sub-systems of process planning and scheduling have been treated sequentially or separately in traditional methods. To increase the effectiveness of system performance, there is an increasing need for deep research and application of integrated process planning and scheduling (IPPS) system. In this paper, a novel two-level genetic algorithm (TGA) is proposed to optimize the IPPS problem. Based on the previous work, deep research should be made on the IPPS problem. In this study, the flow chart of TGA based on the previous integrated optimization strategy has been proposed. Experiment studies have been conducted to verify the performance of the proposed algorithm. The experimental results show that the proposed algorithm for the IPPS is a promising and very effective method.
  • Keywords
    genetic algorithms; process planning; scheduling; IPPS problem; IPPS system; TGA; integrated optimization strategy; integrated process planning and scheduling system; manufacturing system performance; two-level genetic algorithm; Biological cells; Genetic algorithms; Job shop scheduling; Optimization; Process planning; Sociology; Statistics; Process planning; improved genetic algorithm; integrated process planning and scheduling; scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.476
  • Filename
    6722229