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Active scheduling for hybrid flowshop with family setup time and inconsistent family formation

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Abstract

This research is motivated by a real-life hybrid flowshop scheduling problem where jobs are organized in families according to their machine settings and tools. This type of problem is common in the production process of standard metal components. The problem is complicated by the requirement of family setup time when a machine changes from processing one job family to another and the formation of job families varies in different stages. This problem has been previously solved with a non-delay scheduling heuristic in which no machine is kept idle. This research illustrates that inserting intentional idle time into a non-delay schedule can further reduce the total setup time as well as makespan. With the inserted idle time, the non-delay schedules are extended to active schedules. This paper presents a mechanism to determine the locations and lengths of intentional idle times in the efficient active schedules. Four active scheduling approaches are developed by integrating two types of waiting factor operators into two non-delay approaches. Computational experiments have been conducted to compare the proposed active scheduling approaches in terms of effectiveness and efficiency. The results have shown that the proposed active scheduling approaches are superior to non-delay scheduling. The analysis of variance has been applied on the factors related to scheduling environment, problem size and scheduling approach. The analysis has identified factors that are most influential on the scheduling result.

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References

  • Allahverdi, A., Ng, C. T., Cheng, T. C. E., & Kovalyov, M. Y. (2008). A survey of scheduling problems with setup times or costs. European Journal of Operational Research, 187(3), 985–1032.

    Article  Google Scholar 

  • Gen, M., & Cheng, R. (1997). Genetic algorithms and engineering design. New York: Wiley.

    Google Scholar 

  • Goldgerg, D., & Lingle, R. (1985). Alleles, loci, and the traveling salesman problem. Hillsdale: Paper presented at the First international Conference on Genetic Algorithms and their Applications.

  • Gupta, J. N. D., & Schaller, J. E. (2005). Minimizing flow time in a flow-line manufacturing cell with family setup times. Journal of the Operational Research Society, 57(2), 163–176.

    Google Scholar 

  • Kim, H.-W., & Lee, D.-H. (2009). Heuristic algorithms for re-entrant hybrid flow shop scheduling with unrelated parallel machines. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 223(4), 433–442.

    Article  Google Scholar 

  • Lin, B. M. T., & Cheng, T. C. E. (2005). Two-machine flowshop batching and scheduling. Annals of Operations Research, 133, 149–161.

    Article  Google Scholar 

  • Logendran, R., Carson, S., & Hanson, E. (2005). Group scheduling in flexible flow shops. International Journal of Production Economics, 96(2), 143–155.

    Article  Google Scholar 

  • Logendran, R., deSzoeke, P., & Barnard, F. (2006). Sequence-dependent group scheduling problems in flexible flow shops. International Journal of Production Economics, 102(1), 66–86.

    Google Scholar 

  • Luo, H., Huang, G. Q., Shi, Y., Qu, T., & Zhang, Y. (2012). Hybrid flowshop scheduling with family setup time and inconsistent family formation. International Journal of Production Research, 50(6), 1457–1475.

    Google Scholar 

  • Mendes, J. J. M., Gonçalves, J. F., & Resende, M. G. C. (2009). A random key based genetic algorithm for the resource constrained project scheduling problem. Computers & Operations Research, 36(1), 92–109.

    Article  Google Scholar 

  • Michalewicz, Z. (1996). Genetic algorithms+data structures=evolution programs. Berlin: Springer.

    Book  Google Scholar 

  • Mirsanei, H., Zandieh, M., Moayed, M., & Khabbazi, M. (2011). A simulated annealing algorithm approach to hybrid flow shop scheduling with sequence-dependent setup times. Journal of Intelligent Manufacturing, 22(6), 965–978.

    Article  Google Scholar 

  • Pinedo, M. L. (2008). Scheduling: Theory, algorithms, and systems (3rd ed.). Berlin: Springer.

    Google Scholar 

  • Salmasi, N., Logendran, R., & Skandari, M. (2011). Makespan minimization of a flowshop sequence-dependent group scheduling problem. The International Journal of Advanced Manufacturing Technology, 56(5), 699–710.

    Article  Google Scholar 

  • Sprecher, A., Kolisch, R., & Drexl, A. (1995). Semi-active, active, and non-delay schedules for the resource-constrained project scheduling problem. European Journal of Operational Research, 80(1), 94–102.

    Article  Google Scholar 

  • Zandieh, M., Mozaffari, E., & Gholami, M. (2010). A robust genetic algorithm for scheduling realistic hybrid flexible flow line problems. Journal of Intelligent Manufacturing, 21(6), 731–743.

    Article  Google Scholar 

Download references

Acknowledgments

This paper is supported by National Natural Science Foundation of China (51105081), Guangdong Natural Science Foundation (S2012010010016), National Science and Technology Ministry of China (2012BAF12B10), Industry-University-Research Cooperation Key Project of Guangdong Science and Technology Commission (2011B090400409), Guangdong College Talent Import Scheme (11ZK0066), Guangzhou Pearl River New Star Fund Science and Technology Planning Project (2011J2200017), and HKU Seed Funding for Basic Research (201111159135). Partial financial supports from Zhejiang, Hangzhou and Lin’an governments are gratefully acknowledged.

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Correspondence to Hao Luo.

Appendix

Appendix

See Appendix Tables 9,10,11,12.

Table 9 Games-Howell multiple comparisons of SP
Table 10 Games-Howell multiple comparisons of job
Table 11 Games-Howell multiple comparisons of stage
Table 12 Games-Howell multiple comparisons of algorithm

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Luo, H., Zhang, A. & Huang, G.Q. Active scheduling for hybrid flowshop with family setup time and inconsistent family formation. J Intell Manuf 26, 169–187 (2015). https://doi.org/10.1007/s10845-013-0771-9

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  • DOI: https://doi.org/10.1007/s10845-013-0771-9

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