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Hybrid Estimation of Distribution Algorithm for No-Wait Flow-Shop Scheduling Problem with Sequence-Dependent Setup Times and Release Dates

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Intelligent Computing Theories and Application (ICIC 2016)

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Abstract

This paper proposes an innovative hybrid estimation of distribution algorithm (HEDA) for the no-wait flow-shop scheduling problem (NFSSP) with sequence dependent setup times (SDSTs) and release dates (RDs) to minimize the total completion time (TCT), which has been proved to be typically NP-hard combinatorial optimization problem with strong engineering background. Firstly, a speed-up evaluation method is developed according to the property of NFSSP with SDSTs and RDs. Secondly, the genetic information both order of jobs and the promising blocks of jobs are concerned to generate the guided probabilistic model. Thirdly, after the HEDA based global exploration, a problem dependent local search is developed to emphasize exploitation. Due to the reasonable balance between HEDA based global search and problem-dependent local search as well as the comprehensive utilization of the speed-up evaluation, TCT-NFSSP with SDSTs and RDs can be solved effectively and efficiently. Computational results and comparisons demonstrate the superiority of HEDA in terms of searching quality, robustness, and efficiency.

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References

  1. Allahverdi, A.: The third comprehensive survey on scheduling problems with setup times/costs. Eur. J. Oper. Res. 246, 345–378 (2015)

    Article  MathSciNet  Google Scholar 

  2. Allahverdi, A., Ng, C.T., Cheng, T.C.E., Kovalyov, M.Y.: A survey of scheduling problems with setup times or costs. Eur. J. Oper. Res. 187(3), 985–1032 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  3. Bianco, L., Dell’Olmo, P., Giordani, S.: Flow shop no-wait scheduling with sequence dependent setup times and release dates. INFOR 37(1), 3–19 (1999)

    Google Scholar 

  4. Ruiz, R., Stützle, T.: An iterated greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives. Eur. J. Oper. Res. 187(3), 1143–1159 (2008)

    Article  MATH  Google Scholar 

  5. Qian, B., Zhou, H.-B., Hu, R., Xiang, F.-H.: Hybrid differential evolution optimization for no-wait flow-shop scheduling with sequence-dependent setup times and release dates. In: Huang, D.-S., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds.) ICIC 2011. LNCS, vol. 6838, pp. 600–611. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  6. Ding, J.Y., Song, S.J., Gupta, J.N.D., et al.: An improved iterated greedy algorithm with a Tabu-based reconstruction strategy for the no-wait flowshop scheduling problem. Appl. Soft Comput. 30, 604–613 (2014)

    Article  Google Scholar 

  7. Allahverdi, A., Aydilek, H.: Total completion time with makespan constraint in no-wait flowshops with setup times. Eur. J. Oper. Res. 238(1), 724–734 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  8. Samarghandi, H., ElMekkawy, T.Y.: Solving the no-wait flow-shop problem with sequence dependent set-up times. Int. J. Comput. Integr. Manuf. 27(3), 213–228 (2014)

    Article  Google Scholar 

  9. Baluja, S.: Population-based incremental learning: a method for integrating genetic search based function optimization and competitive learning. Technical report CMU-CS-94-193 (1994)

    Google Scholar 

  10. Ceberio, J., Irurozki, E., Mendiburu, A., Lozano, J.A.: A review on estimation of distribution algorithms in permutation-based combinatorial optimization problems. Prog. Artif. Intell. 1(1), 103–117 (2012)

    Article  MATH  Google Scholar 

  11. Pan, Q.K., Ruiz, R.: An estimation of distribution algorithm for lot-streaming flow shop problems with setup times. Omega—Int. J. Manag. Sci. 40(2), 166–180 (2012)

    Article  Google Scholar 

  12. Wang, L., Wang, S.Y., Xu, Y., Zhou, G., Liu, M.: A bi-population based estimation of distribution algorithm for the flexible job-shop scheduling problem. Comput. Ind. Eng. 62, 917–926 (2012)

    Article  Google Scholar 

  13. Wang, S.Y., Wang, L., Liu, M., Xu, Y.: An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem. Int. J. Prod. Econ. 145, 387–396 (2013)

    Article  Google Scholar 

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Acknowledgments

This research was partially supported by the National Science Foundation of China under Grant 60904081, the Applied Basic Research Foundation of Yunnan Province under Grant 2015FB136, the 2012 Academic and Technical Leader Candidate Project for Young and Middle-Aged Persons of Yunnan Province under Grant 2012HB011, and the Discipline Construction Team Project of Kunming University of Science and Technology under Grant 14078212.

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Correspondence to Bin Qian .

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Zhang, ZQ., Qian, B., Hu, R., Zhang, CS., Li, ZH. (2016). Hybrid Estimation of Distribution Algorithm for No-Wait Flow-Shop Scheduling Problem with Sequence-Dependent Setup Times and Release Dates. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_51

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  • DOI: https://doi.org/10.1007/978-3-319-42291-6_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42290-9

  • Online ISBN: 978-3-319-42291-6

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