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A Hybrid Discrete Artificial Bee Colony Algorithm for Multi-objective Blocking Lot-Streaming Flow Shop Scheduling Problem

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Proceedings of 2017 Chinese Intelligent Systems Conference (CISC 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 460))

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Abstract

A blocking lot-streaming flow shop (BLSFS) scheduling problem involves in splitting a job into several sublots and no capacity buffers with blocking between adjacent machines. It is of popularity in real-world applications but hard to be effectively solved in light of many constrains and complexities. Thus, the research on optimization algorithms for the BLSFS scheduling problem is relatively scarce. In view of this, we proposed a hybrid discrete artificial bee colony (HDABC) algorithm to tackle the BLSFS scheduling problem with two commonly used and conflicting criteria, i.e., makespan and earliness time. We first presented three initialization strategies to enhance the quality of the initial population, and then developed two novel crossover operators by taking full of valuable information of non-dominated solutions to enhance the capabilities of HDABC in exploration. We applied the proposed algorithm to 16 instances and compared with three previous algorithms. The experimental results show that the proposed algorithm clearly outperforms these comparative algorithms.

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References

  1. Behnamian J, Ghomi SMTF, Zandieh M. A multi-phase covering pareto-optimal front method to multi-objective scheduling in a realistic hybrid flowshop using a hybrid metaheuristic. Expert Syst Appl. 2009;36(8):11057–69.

    Article  Google Scholar 

  2. Chang PC. A pareto block-based estimation and distribution algorithm for multi-objective permutation flow shop scheduling problem. Int J Prod Res. 2015;53(3):793–834.

    Article  Google Scholar 

  3. Han YY, Gong DW, Sun XY, Pan QK. An improved nsga-ii algorithm for multi-objective lot-streaming flow shop scheduling problem. Int J Prod Res. 2014;52(8):2211–31.

    Article  Google Scholar 

  4. Kalir AA, Sarin SC. Evaluation of the potential benefits of lot streaming in flow-shop systems. Int J Prod Econ. 2000;66(2):131–42.

    Article  Google Scholar 

  5. Marimuthu S, Ponnambalam SG, Jawahar N. Threshold accepting and ant-colony optimization algorithms for scheduling m-machine flow shops with lot streaming. J Mater Process Tech. 2009;209(2):1026–41.

    Article  Google Scholar 

  6. Martin CH. A hybrid genetic algorithm/mathematical programming approach to the multi-family flowshop scheduling problem with lot streaming. Omega. 2009;37(1):126–37.

    Article  Google Scholar 

  7. Mhlenbein H, Paa G. From recombination of genes to the estimation of distributions I. Binary parameters. Berlin Springer; 1996.

    Google Scholar 

  8. Pan QK, Ruiz R. An estimation of distribution algorithm for lot-streaming flow shop problems with setup times. Omega. 2012;40(2):166–80.

    Article  Google Scholar 

  9. Pan QK, Wang L, Qian B. A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems. Comput Oper Res. 2009;36(8):2498–511.

    Article  MathSciNet  MATH  Google Scholar 

  10. Ronconi DP. A note on constructive heuristics for the flowshop problem with blocking. Int J Prod Econ. 2004;87(1):39–48.

    Article  Google Scholar 

  11. Tseng CT, Liao CJ. A discrete particle swarm optimization for lot-streaming flowshop scheduling problem. Eur J Oper Res. 2008;191(2):360–373

    Google Scholar 

  12. Ventura JA, Yoon SH. A new genetic algorithm for lot-streaming flow shop scheduling with limited capacity buffers. J Intell Manuf. 2013;24(6):1185–96.

    Article  Google Scholar 

  13. Yoon SH, Ventura JA. An application of genetic algorithms to lot-streaming flow shop scheduling. IIE Trans. 2002;34(9):779–87.

    Google Scholar 

  14. Zhang W, Yin C, Liu J, Linn RJ. Multi-job lot streaming to minimize the mean completion time in m -1 hybrid flowshops. Intern J Prod Econ. 2005;96(2):189–200.

    Article  Google Scholar 

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Acknowledgements

This research is partially supported by Natural Science Foundation of China under Grant number 61375067, 61473299.

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Authors and Affiliations

  1. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Dunwei Gong

  2. School of Computer Science, Liaocheng University, Liaocheng, 252000, China

    Yuyan Han

  3. School of Mathematics and Statistics, Xian Jiaotong University, Xian, 710049, China

    Jianyong Sun

Authors
  1. Dunwei Gong
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  2. Yuyan Han
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  3. Jianyong Sun
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Corresponding author

Correspondence to Yuyan Han .

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Editors and Affiliations

  1. Beihang University , Beijing, China

    Yingmin Jia

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  3. University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

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© 2018 Springer Nature Singapore Pte Ltd.

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Gong, D., Han, Y., Sun, J. (2018). A Hybrid Discrete Artificial Bee Colony Algorithm for Multi-objective Blocking Lot-Streaming Flow Shop Scheduling Problem. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2017 Chinese Intelligent Systems Conference. CISC 2017. Lecture Notes in Electrical Engineering, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-6499-9_57

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  • DOI: https://doi.org/10.1007/978-981-10-6499-9_57

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6498-2

  • Online ISBN: 978-981-10-6499-9

  • eBook Packages: EngineeringEngineering (R0)

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