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A Sustainable Model of Flow Shop Scheduling for High-Efficiency, Energy-Saving and Low-Cost

  • Liming WangEmail author
  • Xinyue Liu
  • Lin Kong
  • Fangyi Li
  • Jianfeng Li
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 130)

Abstract

With the aggravation of economic and environmental pressure, the shop scheduling method cannot deal with the problem that high-efficiency, energy-saving and low-cost demands of current manufacturing industry. To solve this problem, this paper proposed an elaborated sustainable model for the flow-shop scheduling through modeling the production time, energy consumption and production cost with multi-objective optimization which was solve using a modified genetic algorithm combined with AHP analysis. Finally, a case study about the piston shop-scheduling was carried out by comparing various scheduling schemes to verify the validity and practicality.

Keywords

Flow-shop scheduling Sustainable production Multi-objective Genetic algorithm 

Notes

Acknowledgement

This work was partially supported by the Shandong Provincial Natural Science Foundation, China (ZR2017BEE018), China Postdoctoral Science Foundation (2016M592182) and the Natural Science Foundation of China (51675314).

References

  1. 1.
    Taisch, M.: Multi-objective genetic algorithm for energy-efficient job shop scheduling. Int. J. Prod. Res. 53(23), 7071–7089 (2015)CrossRefGoogle Scholar
  2. 2.
    Veleva, V., Ellenbecker, M.: Indicators of sustainable production: framework and methodology. J. Clean. Prod. 9(6), 519–549 (2001)CrossRefGoogle Scholar
  3. 3.
    Ma, J., Lei, Y., Wang, Z., et al.: A Memetic algorithm based on Immune multi-objective optimization for flexible job-shop scheduling problems. In: IEEE Congress on Evolutionary Computation, pp. 58–65 (2014)Google Scholar
  4. 4.
    Cost, A., Cappadonna, F.A., Fichera, S.: Joint optimization of a flow-shop group scheduling with sequence dependent set-up times and skilled workforce assignment. Int. J. Prod. Res. 52(9), 2696–2728 (2014)CrossRefGoogle Scholar
  5. 5.
    Liou, C.D., Hsieh, Y.C.: A hybrid algorithm for the multi-stage flow shop group scheduling with sequence-dependent setup and transportation times. Int. J. Prod. Econ. 170, 258–267 (2015)CrossRefGoogle Scholar
  6. 6.
    Samarghandi, H., Elmekkawy, T.Y.: A genetic algorithm and particle swarm optimization for no-wait flow shop problem with separable setup times and makespan criterion. Int. J. Adv. Manuf. Technol. 61(9–12), 1101–1114 (2012)CrossRefGoogle Scholar
  7. 7.
    Ruiz, R., Maroto, C., Alcaraz, J.: Solving the flowshop scheduling problem with sequence dependent setup times using advanced metaheuristics. Eur. J. Oper. Res. 165(1), 34–54 (2005)CrossRefGoogle Scholar
  8. 8.
    Nishi, T., Hiranaka, Y.: Lagrangian relaxation and cut generation for sequence-dependent setup time flowshop scheduling problems to minimise the total weighted tardiness. Int. J. Prod. Res. 51(16), 4778–4796 (2013)CrossRefGoogle Scholar
  9. 9.
    Dai, M., Tang, D., Giret, A., et al.: Energy-efficient scheduling for a flexible flow shop using an improved genetic-simulated annealing algorithm. Robot. Comput.-Integr. Manuf. 29(5), 418–429 (2013)CrossRefGoogle Scholar
  10. 10.
    Mansouri, S.A., Aktas, E., Besikci, U.: Green scheduling of a two-machine flowshop: trade-off between makespan and energy consumption. Eur. J. Oper. Res. 248(3), 772–788 (2016)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Liu, X., Xie, L., Tao, Z., et al.: Flexible job shop scheduling for decreasing production costs. J. Northeastern Univ. 29(4), 561–564 (2008)zbMATHGoogle Scholar
  12. 12.
    Zhang, H., Zhao, F., Sutherland, J.W.: Scheduling of a single flow shop for minimal energy cost under real-time electricity pricing. J. Manuf. Sci. Eng. 139(1) (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Liming Wang
    • 1
    • 2
    Email author
  • Xinyue Liu
    • 1
    • 2
  • Lin Kong
    • 1
    • 2
  • Fangyi Li
    • 1
    • 2
  • Jianfeng Li
    • 1
    • 2
  1. 1.Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical EngineeringShandong UniversityJinanChina
  2. 2.National Demonstration Center for Experimental Mechanical Engineering EducationShandong UniversityJinanChina

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