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Improved DE search for competing groups scheduling with deterioration effects

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Abstract

This paper investigates a three-competing group scheduling problem on serial-batching machines considering the setup time of groups and batches, as well as the job-dependent deteriorating effect, where the setup time of groups and batches depends on their own corresponding start time and deterioration rate, and the jobs’ actual processing time depends on their starting time and deterioration rate. In this problem, the jobs in three groups are processed competitively, and the jobs belonging to the same group are processed together on a machine, meanwhile, the jobs from each group are divided into batches. The objective is to minimize the makespan of one group with deterioration effect under the constraint of satisfying the threshold value of another group. Some key structural properties are proposed under the relevant demonstration, and a decision flow chart of scheduling rules is constructed based on these structural properties. Then, an effective improved differential evolution (DE) search algorithm combining the shaking operation from variable neighborhood search is developed to solve the studied scheduling problem. Computational experiments are conducted to evaluate the performance of proposed improved DE algorithm and some other well-known algorithms. The experimental results show that the proposed algorithm is more effective and stable than compared algorithms.

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References

  1. Webster, S., Baker, K.R.: Scheduling groups of jobs on a single machine. Oper. Res. 43, 692–703 (1995)

    Article  MathSciNet  Google Scholar 

  2. Kuo, W.H., Yang, D.L.: Minimizing the total completion time in a single-machine scheduling problem with a time-dependent learning effect. Eur. J. Oper. Res. 174, 1184–1190 (2006)

    Article  MathSciNet  Google Scholar 

  3. Wu, W.H.: Solving a two-agent single-machine learning scheduling problem. Int. J. Comput. Integr. Manuf. 27, 20–35 (2014)

    Article  Google Scholar 

  4. Li, D., Hsu, P.: Solving a two-agent single-machine scheduling problem considering learning effect. Comput. Oper. Res. 39, 1644–1651 (2012)

    Article  MathSciNet  Google Scholar 

  5. Woo, Y.B., Byung, S.K.: Matheuristic approaches for parallel machine scheduling problem with time-dependent deterioration and multiple rate-modifying activities. Comput. Oper. Res. 95, 97–112 (2018)

    Article  MathSciNet  Google Scholar 

  6. Sun, X., Xin, N.: Single-machine scheduling with deteriorating effects and machine maintenance. Int. J. Prod. Res. 57(10), 1–14 (2019)

    Article  Google Scholar 

  7. Lu, Y.Y.: Research on no-idle permutation flow shop scheduling with time-dependent learning effect and deteriorating jobs. Appl. Math. Model. 40(4), 3447–3450 (2016)

    Article  MathSciNet  Google Scholar 

  8. Yang, S.W., Wan, L., Yin, N.: Research on single machine SLK/DIF due window assignment problem with learning effect and deteriorating jobs. Appl. Math. Model. 39(15), 4593–4598 (2015)

    Article  MathSciNet  Google Scholar 

  9. Yue, Q., Wan, G.: Single machine SLK/DIF due window assignment problem with job-dependent linear deterioration effects. J. Oper. Res. Soc. 67(6), 872–883 (2016)

    Article  Google Scholar 

  10. Su, L.H., Wang, H.M.: Minimizing total absolute deviation of job completion times on a single machine with cleaning activities. Comput. Ind. Eng. 103, 242–249 (2017)

    Article  Google Scholar 

  11. Zhang, X., Wu, W.H., Lin, W.C., Wu, C.C.: Machine scheduling problems under deteriorating effects and deteriorating rate-modifying activities. J. Oper. Res. Soc. 69(3), 439–448 (2017)

    Article  Google Scholar 

  12. Kong, M., Liu, X., Pei, J., Zhou, Z., Pardalos, P.M.: Parallel-batching scheduling of deteriorating jobs with non-identical sizes and rejection on a single machine. Optim. Lett. (2019). https://doi.org/10.1007/s11590-019-01389-x

    Article  MATH  Google Scholar 

  13. Pei, J., Song, Q., Liao, B., Liu, X., Pardalos, P.M.: Parallel-machine serial-batching scheduling with arbitrary release times under the effects of position-dependent learning and time-dependent deterioration. Ann. Oper. Res. (2020). https://doi.org/10.1007/s10479-020-03555-2

    Article  Google Scholar 

  14. Liu, X., Lu, S., Pei, J., Pandalos, P.M.: A hybrid VNS-HS algorithm for a supply chain scheduling problem with deteriorating jobs. Int. J. Prod. Res. 56(17), 5758–5775 (2018)

    Article  Google Scholar 

  15. Pei, J., Pardalos, P.M., Liu, X., Fan, W., Yang, S.: Serial batching scheduling of deteriorating jobs in a two-stage supply chain to minimize the makespan. Eur. J. Oper. Res. 244(1), 13–25 (2015)

    Article  MathSciNet  Google Scholar 

  16. Pei, J., Liu, X., Pardalos, P.M., Fan, W., Yang, S.: Single machine serial-batching scheduling with independent setup time and deteriorating job processing times. Optim. Lett. 9(1), 91–104 (2015)

    Article  MathSciNet  Google Scholar 

  17. Pei, J., Liu, X., Pardalos, P.M., Fan, W., Yang, S.: Scheduling deteriorating jobs on a single serial batching machine with multiple job types and sequence-dependent setup times. Ann. Oper. Res. 249, 175–195 (2017)

    Article  MathSciNet  Google Scholar 

  18. Pei, J., Liu, X., Pardalos, P.M., Migdalas, A., Yang, S.: Serial-batching scheduling with time-dependent setup time and effects of deterioration and learning on a single-machine. J. Glob. Optim. 67(1), 251–262 (2017)

    Article  MathSciNet  Google Scholar 

  19. Pei, J., Liu, X., Fan, W., Pardalos, P.M., Lu, S.: A hybrid BA-VNS algorithm for coordinated serial batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers. Omega 2019, 55–69 (2019)

    Article  Google Scholar 

  20. Liao, B., Pei, J., Yang, S., Pardalos, P.M., Lu, S.: Single-machine and parallel-machine parallel-batching scheduling considering deteriorating jobs, various group, and time-dependent setup time. Informatica 29, 281–301 (2018)

    Article  MathSciNet  Google Scholar 

  21. Liao, B., Song, Q., Pei, J., Yang, S., Pardalos, P.M.: Parallel-machine group scheduling with inclusive processing set restrictions, outsourcing option and serial-batching under the effect of step-deterioration. J. Glob. Optim. (2018). https://doi.org/10.1007/s10898-018-0707-1

    Article  Google Scholar 

  22. Storn, R., Price, K.: Differential evolution––a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11(4), 341–359 (1997)

    Article  MathSciNet  Google Scholar 

  23. Wu, X., Che, A.: A memetic differential evolution algorithm for energy-efficient parallel machine scheduling. Omega 82, 155–165 (2019)

    Article  Google Scholar 

  24. Zhou, S., Li, X., Du, N., Pang, Y., Chen, H.: A multi-objective differential evolution algorithm for parallel batch processing machine scheduling considering electricity consumption cost. Comput. Oper. Res. 96, 55–68 (2018)

    Article  MathSciNet  Google Scholar 

  25. Zhang, G., Xing, K., Cao, F.: Discrete differential evolution algorithm for distributed blocking flowshop scheduling with makespan criterion. Eng. Appl. Artif. Intell. 76, 96–107 (2019)

    Article  Google Scholar 

  26. Zhang, G., Xing, K.: Differential evolution metaheuristics for distributed limited-buffer flowshop scheduling with makespan criterion. Comput. Oper. Res. 108, 33–43 (2019)

    Article  MathSciNet  Google Scholar 

  27. Valentino, S., Marco, B., Alfredo, M.: Algebraic differential evolution algorithm for the permutation flowshop scheduling problem with total flowtime criterion. IEEE Trans. Evol. Comput. 20(5), 682–694 (2015)

    Google Scholar 

  28. Kumar, N., Vidyarthi, D.P.: A novel hybrid PSO–GA meta-heuristic for scheduling of DAG with communication on multiprocessor systems. Eng. Comput. 32(1), 35–47 (2016)

    Article  Google Scholar 

  29. Armas, J., Lalla-Ruiz, E., Expósito-Izquierdo, C., Landa-Silva, D., Melián-Batista, B.: A hybrid GRASP-VNS for ship routing and scheduling problem with discretized time windows. Eng. Appl. Artif. Intell. 45, 350–360 (2015)

    Article  Google Scholar 

  30. Xiong, F., Xing, K.: Meta-heuristics for the distributed two-stage assembly scheduling problem with bi-criteria of makespan and mean completion time. Int. J. Prod. Res. 52(9), 2743–2766 (2014)

    Article  Google Scholar 

  31. Pei, J., Liu, X., Pardalos, P.M., Fan, W., Yang, S., Wang, L.: Application of an effective modified gravitational search algorithm for the coordinated scheduling problem in a two-stage supply chain. Int. J. Adv. Manuf. Technol. 70(1–4), 335–348 (2014)

    Article  Google Scholar 

  32. Vallada, E., Ruiz, R.: A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times. Eur. J. Oper. Res. 211(3), 612–622 (2011)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 71690230, 71690235).

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Correspondence to Baoyu Liao.

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Appendix

Appendix

See Tables 3, 4 and Figs. 5, 6, 7.

Table 3 Overview of scheduling problems with learning effect
Table 4 Notations
Fig. 5
figure 5

The framework of the scheduling problem

Fig. 6
figure 6

The judgment flow chart of the group sequences

Fig. 7
figure 7figure 7figure 7

The pseudo-code of improved-DE algorithm

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Liao, B., Wang, H., Zhu, X. et al. Improved DE search for competing groups scheduling with deterioration effects. Optim Lett 15, 469–494 (2021). https://doi.org/10.1007/s11590-020-01581-4

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