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A Two-Phase Variable Neighborhood Search for Flexible Job Shop Scheduling Problem with Energy Consumption Constraint

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Intelligent Computing Theories and Application (ICIC 2018)

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Abstract

This paper investigates flexible job shop scheduling problem (FJSP) with energy consumption constraint, the goal of which is to minimize makespan and total tardiness under the constraint that total energy consumption doesn’t exceed a given threshold. Energy consumption constraint is not always met and a new method for this constraint is proposed. A two-phase variable neighborhood search (TVNS) is presented. In the first phase, the problem is converted into FJSP with makespan, total tardiness and total energy consumption and a VNS is applied for the new problem. In the second phase, another VNS is for the original problem by strategies for comparing solutions and updating the non-dominated set \( \Omega \) of the first phase. The current solution of TVNS is replaced with a member of \( \Omega \) every a prefixed number of iterations to improve solution quality. Extensive experiments are conducted and computational results validate the effectiveness and advantages of TVNS for the considered FJSP.

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References

  1. Kacem, I., Hammadi, S., Borne, P.: Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic. Math. Comput. Simul. 60(3–5), 245–276 (2002)

    Article  MathSciNet  Google Scholar 

  2. Gao, J., Gen, M., Sun, L., Zhao, X.: A hybrid of genetic algorithm and bottleneck shifting for multi-objective flexible job shop scheduling problems. Comput. Ind. Eng. 53(1), 149–162 (2007)

    Article  Google Scholar 

  3. Yuan, Y., Xu, H.: Multiobjective flexible job shop scheduling using memetic algorithms. IEEE Trans. Autom. Sci. Eng. 12(1), 336–353 (2015)

    Article  Google Scholar 

  4. Rohaninejad, M., Kheirkhah, A., Fattahi, P., Vahedi-Nouri, B.: A hybrid multi-objective genetic algorithm based on the ELECTRE method for a capacitated flexible job shop scheduling problem. Int. J. Adv. Manufact. Technol. 77(1), 51–66 (2015)

    Article  Google Scholar 

  5. Rohaninejad, M., Sahraeian, R., Nouri, B.V.: Multi-objective optimization of integrated lot-sizing and scheduling problem in flexible job shop. PAIRO Oper. Res. 50(3), 587–609 (2015)

    MathSciNet  MATH  Google Scholar 

  6. Li, J., Huang, Y., Niu, X.: A branch population genetic algorithm for dual-resource constrained job shop scheduling problem. Comput. Ind. Eng. 102(1), 113–131 (2016)

    Article  Google Scholar 

  7. Ahmadi, E., Zandieh, M., Farrokh, M., Emami, S.M.: A multi objective optimization approach for flexible job shop scheduling problem under random machine breakdown by evolutionary algorithm. Comput. Oper. Res. 73(1), 56–66 (2016)

    Article  MathSciNet  Google Scholar 

  8. Shen, X.N., Han, Y., Fu, J.Z.: Robustness measures and robust scheduling for multi-objective stochastic flexible job shop scheduling problems. Soft Comput. (2018, in press)

    Google Scholar 

  9. Moslehi, G., Mahnam, M.: A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search. Int. J. Prod. Econ. 129(1), 14–22 (2011)

    Article  Google Scholar 

  10. Singh, M.R., Singh, M., Mahapatra, S.S., Jagadev, N.: Particle swarm optimization algorithm embedded with maximum deviation theory for solving multi-objective flexible job shop scheduling problem. Int. J. Adv. Manuf. Technol. 85(9), 2353–2366 (2016)

    Article  Google Scholar 

  11. Gao, K.Z., Suganthan, P.N., Pan, Q.K., Chua, T.J., Cai, T.X., Chong, C.S.: Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling. Inf. Sci. 289(1), 76–90 (2014)

    Article  MathSciNet  Google Scholar 

  12. Li, J.Q., Pan, Q.K., Tasgetiren, M.F.: A discrete artificial bee colony algorithm for the multi-objective flexible job-shop scheduling problem with maintenance. Appl. Math. Model. 38(3), 1111–1132 (2014)

    Article  MathSciNet  Google Scholar 

  13. Jia, S., Hu, Z.H.: Path-relinking tabu search for the multi-objective flexible job shop scheduling problem. Comput. Oper. Res. 47(1), 11–26 (2014)

    Article  MathSciNet  Google Scholar 

  14. Bagheri, A., Zandieh, M.: Bi-criteria flexible job-shop scheduling with sequence-dependent setup times-variable neighborhood search approach. J. Manuf. Syst. 30(1), 8–15 (2011)

    Article  Google Scholar 

  15. Li, J.Q., Pan, Q.K., Xie, S.X.: An effective shuffled frog-leaping algorithm for multi-objective flexible job shop scheduling problems. Appl. Math. Comput. 218(18), 9353–9371 (2012)

    MathSciNet  MATH  Google Scholar 

  16. Wang, L., Wang, S.Y., Liu, M.: A Pareto-based estimation of distribution algorithm for the multi-objective flexible job-shop scheduling problem. Int. J. Prod. Res. 51(12), 3574–3592 (2013)

    Article  Google Scholar 

  17. Li, J.Q., Sang, H.Y., Han, Y.Y., Wang, C.G., Gao, K.Z.: Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions. J. Cleaner Prod. 181, 584–598 (2018)

    Article  Google Scholar 

  18. He, Y., Li, Y.F., Wu, T., Sutherland, J.W.: An energy-responsive optimization method for machine tool selection and operation sequence in flexible machining job shops. J. Cleaner Prod. 87(1), 245–254 (2015)

    Article  Google Scholar 

  19. Yin, L.J., Li, X.Y., Gao, L., Lu, C., Zhang, Z.: A novel mathematical model and multi-objective method for the low-carbon flexible job shop scheduling problem. Sustain. Comput. Inf. Syst. 13, 15–30 (2017)

    Google Scholar 

  20. Lei, D.M., Zheng, Y.L., Guo, X.P.: A shuffled frog leaping algorithm for flexible job shop scheduling with the consideration of energy consumption. Int. J. Prod. Res. 55(11), 3126–3140 (2017)

    Article  Google Scholar 

  21. Mokhtari, H., Hasani, A.: An energy-efficient multi-objective optimization for flexible job shop scheduling. Comput. Ind. Eng. 104, 339–352 (2017)

    Google Scholar 

  22. Lei, D.M., Li, M., Wang, L.: A two-phase meta-heuristic for multi-objective flexible job shop scheduling problem with total energy consumption threshold. IEEE Trans. Cybern. (2018, in press)

    Google Scholar 

  23. Lei, D.M., Yang, D.J.: Research on flexible job shop scheduling problem with total energy consumption constraint. ACTA Autom. Sinica (2018, in press). (in Chinese)

    Google Scholar 

  24. Lei, D.M.: Simplified multi-objective genetic algorithm for stochastic job shop scheduling. Appl. Soft Comput. 11(8), 4991–4996 (2011)

    Article  Google Scholar 

  25. Dauzère-Pérès, S., Paulli, J.: An integrated approach for modeling and solving the general multiprocessor job-shop scheduling problem using tabu search. Ann. Oper. Res. 70(2), 281–306 (1997)

    Article  MathSciNet  Google Scholar 

  26. Knowles, J.D., Corne, D.W.: On metrics for comparing non-dominated sets. In: Proceedings of 2002 Congress on Evolutionary Computation, Honolulu, 12–17 May, pp. 711–716 (2002)

    Google Scholar 

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Acknowledgement

This work is supported by the National Natural Science of Foundation of China (61573264).

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Authors and Affiliations

  1. School of Automation, Wuhan University of Technology, Wuhan, 430070, China

    Chengzhi Guo & Deming Lei

Authors
  1. Chengzhi Guo
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  2. Deming Lei
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Corresponding author

Correspondence to Deming Lei .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Polytechnic of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

  4. Indian Institute of Technology Kanpur, Kanpur, India

    Phalguni Gupta

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Guo, C., Lei, D. (2018). A Two-Phase Variable Neighborhood Search for Flexible Job Shop Scheduling Problem with Energy Consumption Constraint. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10954. Springer, Cham. https://doi.org/10.1007/978-3-319-95930-6_72

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  • DOI: https://doi.org/10.1007/978-3-319-95930-6_72

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95929-0

  • Online ISBN: 978-3-319-95930-6

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