• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2018, Vol. 54 ›› Issue (9): 45-54.doi: 10.3901/JME.2018.09.045

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Energy-saving Oriented Multi-objective Shop Floor Scheduling for Mixed-line Production of Missile Components

WEI Xin1, ZHANG Zequn1, TANG Dunbing1, YANG Changqi2, JIN Yongqiao2, QIN Wei3   

  1. 1. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016;
    2. Shanghai Spaceflight Precision Machinery Institute, Shanghai Academy of Spaceflight Technology, Shanghai 201600;
    3. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240
  • Received:2017-08-02 Revised:2018-01-10 Online:2018-05-05 Published:2018-05-05

Abstract: Aimed at the characteristics of multi-project production, complex process, high energy consumption and tight delivery in the mix-line production of missile structural components, an optimization model for a flexible job-shop scheduling problem considering energy consumption and makespan is developed based on equipment state-energy-consumption curve. A binary hybrid improved genetic algorithm (BH-GA) is proposed to solve the established optimization problem. To improve the searching ability of the algorithm, an information-sharing mechanism based on particle swarm optimization (PSO) is introduced to design the crossover operation of genetic algorithm (GA). In order to avoid falling into local optical solution, a novel temperature update function of simulated annealing algorithm (SA) based on Hill function is used to replace the mutation operation of GA. In addition, a weighted multi-attribute grey target decision model is adopted to select the most satisfactory schedule scheme. The effectiveness of the proposed algorithm is verified by the completely and partially flexible scheduling problems. Finally, the proposed algorithm is applied to the production workshop of missile structural components at an aerospace institute in Shanghai, and good effect is gained.

Key words: binary hybrid improved genetic algorithm, energy consumption, equipment state-energy-consumption curve, flexible job-shop, weighted multi-attribute grey target decision model

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