Skip to main content
Log in

Maintenance Scheduling Problem with Fuzzy Random Time Windows on a Single Machine

  • Research Article - Systems Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

This work developed an integrated scheduling model which incorporated both production scheduling and maintenance planning for a single machine problem and considered the multiple objectives of minimizing total weighted completion time and maximizing average timeliness level under a fuzzy environment. First, a fuzzy random variable for maintenance time windows was considered, and this model was then transformed using the expected value. Finally, a numerical example was used to demonstrate the value of this improved algorithm, the computational results from which proved its efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Lin Y.K.: Scheduling identical jobs on uniform parallel machines under position-based learning effects. Arab. J. Sci. Eng. 39(8), 6567–6574 (2014)

    Article  Google Scholar 

  2. Yu X., Zhang Y.: Single machine scheduling with aging effect and upper-bounded actual processing times. Arab. J. Sci. Eng. 39(2), 1489–1495 (2014)

    Article  MathSciNet  Google Scholar 

  3. Adiri I., Frostig E., Kan A.H.G.: Scheduling on a single machine with a single breakdown to minimize stochastically the number of tardy jobs. Nav. Res. Logist. 38(2), 261–271 (1991)

    Article  MATH  Google Scholar 

  4. Haddad H.: Minimizing total weighted tardiness and earliness on a single machine production scheduling problem with multi-task maintenance policy and deteriorating jobs. Arab. J. Sci. Eng. 39(8), 6543–6553 (2014)

    Article  Google Scholar 

  5. Lee C.Y., Liman S.D.: Single machine flow-time scheduling with scheduled maintenance. Acta Inform. 29, 375–382 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  6. Qi, X., Chen, T., Tu, F.: Scheduling the maintenance on a single machine. J. Oper. Res. Soc. pp. 1071–1078 (1999)

  7. Liao C.J., Chen W.J.: Single-machine scheduling with periodic maintenance and nonresemable jobs. Comput. Oper. Res. 30, 1335–1347 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  8. Chen J.S.: Optimization models for the machine scheduling problem with a single flexible maintenance activity. Eng. Optim. 38(1), 53–71 (2006)

    Article  MathSciNet  Google Scholar 

  9. Xu D., Liu A., Yang D.L.: Mathematical programming models for competitive two-agent single-machine scheduling with flexible periodic maintenance activities. Arab. J. Sci. Eng. 39(5), 3715–3722 (2014)

    Article  MathSciNet  Google Scholar 

  10. Kaplanoglu V.: Multi-agent based approach for single machine scheduling with sequence-dependent setup times and machine maintenance. Appl. Soft Comput. 23, 165–179 (2014)

    Article  Google Scholar 

  11. Yang D.L., Hung C.L., Hsu C.J., Chern M.S.: Minimizing the makespan in a single machine scheduling problem with a flexible maintenance. J. Chin. Inst. Ind. Eng. 19(1), 63–66 (2002)

    Google Scholar 

  12. Chen J.S.: Scheduling of nonresumable jobs and flexible maintenance activities on a single machine to minimize makespan. Eur. J. Oper. Res. 190(1), 90–102 (2008)

    Article  MATH  Google Scholar 

  13. Fitouhi M.C., Nourelfath M.: Integrating noncyclical preventive maintenance scheduling and production planning for a single machine. Int. J. Prod. Econ. 136(2), 344–351 (2012)

    Article  Google Scholar 

  14. Li J.Q., Pan Q.K.: Chemical-reaction optimization for flexible job-shop scheduling problems with maintenance activity. Appl. Soft Comput. 12(9), 2896–2912 (2012)

    Article  MathSciNet  Google Scholar 

  15. Gao J., Gen M., Sun L.: Scheduling jobs and maintenances in flexible job shop with a hybrid genetic algorithm. J. Intell. Manuf. 17(4), 493–507 (2006)

    Article  Google Scholar 

  16. Li J.Q., Pan Q.K.: Chemical-reaction optimization for solving fuzzy job-shop scheduling problem with flexible maintenance activities. Int. J. Prod. Econ. 145(1), 4–17 (2013)

    Article  Google Scholar 

  17. Zadeh L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  18. Xu J.P., Zhou X.Y.: Fuzzy-Like Multiple Objective Decision Making. Springer, Berlin (2011)

    MATH  Google Scholar 

  19. Ghadimi N., Afkousi-Paqaleh A., Emamhosseini A.: A PSO-based fuzzy long-term multi-objective optimization approach for placement and parameter setting of UPFC. Arab. J. Sci. Eng. 39(4), 2953–2963 (2014)

    Article  Google Scholar 

  20. Vahidi H., Ghazban F., Abdoli M.A., Kazemi V.D., Banaei S.M.A.: Fuzzy analytical hierarchy process disposal method selection for an industrial state; case study Charmshahr. Arab. J. Sci. Eng. 39(2), 725–735 (2014)

    Article  Google Scholar 

  21. Xu J., Yan F., Li S.: Vehicle routing optimization with soft time windows in a fuzzy random environment. Transp. Res. Part E: Logist. Transp. Rev. 47(6), 1075–1091 (2011)

    Article  Google Scholar 

  22. Wang, D.; Xu, J.P.: A fuzzy multi-objective optimizing scheduling for operation room in hospital. In: Proceedings of the 2008 International Conference on Industrial Engineering and Engineering Management, pp. 914–918 (2008)

  23. Tang J., Pan Z., Fung R.Y., Lau H.: Vehicle routing problem with fuzzy time windows. Fuzzy Sets Syst. 160(5), 683–695 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  24. Low C., Ji M., Hsu C.J.; et al.: Minimizing the makespan in a single machine scheduling problems with flexible and periodic maintenance. Appl. Math. Model. 34(2), 334–342 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  25. Vahedi Nouri, B., Fattahi, P., Ramezanian, R.: Hybrid firefly-simulated annealing algorithm for the flow shop problem with learning effects and flexible maintenance activities. Int. J. Prod. Res. (ahead-of-print) pp. 1–15 (2013)

  26. Kruse, R.; Meyer, K.D.: Statistics with Vague Data (vol. 6). Springer, Berlin (1987)

  27. Heilpern S.: The expected value of a fuzzy number. Fuzzy Sets Syst. 47(1), 81–86 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  28. Kennedy, J.; Eberhart, R.: Particle swarm optimization. In: Proceedings of the IEEE Conference on Neural Networks, Piscataway, NJ, USA (1995)

  29. Jayabarathi T., Kolipakula R.T., Krishna M.V., Yazdani A.: Application and comparison of PSO, its variants and HDE techniques to emission/economic dispatch. Arab. J. Sci. Eng. 39(2), 967–976 (2014)

    Article  Google Scholar 

  30. Qi, J.J.; Liu, Y.J.; Lei, H.T.; Guo, B.: Solving the multi-mode resource availability cost problem in project scheduling based on modified particle swarm optimization. Arab. J. Sci. Eng. pp. 1–10 (2014)

  31. Sadrzadeh A.: Development of both the AIS and PSO for solving the flexible job shop scheduling problem. Arab. J. Sci. Eng. 38(12), 3593–3604 (2013)

    Article  Google Scholar 

  32. Yang C.I., Chou J.H., Chang C.K.: Hybrid Taguchi-based particle swarm optimization for flowshop scheduling problem. Arab. J. Sci. Eng. 39(3), 2393–2412 (2014)

    Article  Google Scholar 

  33. Park, Y.S.; Kim, J.H.; Park, J.H.; Hong, J.H.: Generating unit maintenance scheduling using hybrid PSO algorithm. In: Intelligent Systems Applications to Power Systems, 2007. International Conference. 1–6. IEEE (2007)

  34. Pereira C.M., Lapa C.M., Mol A.C., Da Luz A.F.: A particle swarm optimization (PSO) approach for non-periodic preventive maintenance scheduling programming. Prog. Nucl. Energy 52(8), 710–714 (2010)

    Article  Google Scholar 

  35. Ai T.J., Kachitvichyanukul V.: A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery. Comput. Oper. Res. 36, 1693–1702 (2009)

    Article  MATH  Google Scholar 

  36. Bays C.: A comparison of next-fit, first-fit, and best-fit. Commun. ACM 20(3), 191–192 (1977)

    Article  Google Scholar 

  37. Veeramachaneni, K.; Peram, T.; Mohan, C.; Osadciw, L.A.: Optimization using particle swarms with near neighbor interactions. In: Genetic and Evolutionary Computation-GECCO 2003 (pp. 110–121). Springer, Berlin (2003)

  38. Pinedo M.: Scheduling: Theory, Algorithms and Systems. Springer, Berlin (2012)

    Book  Google Scholar 

  39. Garey M.R., Johnson D.S.: Approximation algorithms for bin packing problems: a survey. Anal. Des. Algorithms Comb. Optim. 266, 147–172 (1981)

    Google Scholar 

  40. Li B.B., Wang L.: A hybrid quantum-inspired genetic algorithm for multi-objective flow shop scheduling. IEEE Trans. Syst. Man. Cybern. B 37, 576–591 (2007)

    Article  Google Scholar 

  41. Vanden Bergh F., Engelbrecht A.P.: A convergence proof for the particle swarm optimiser. Fundam. Inform. 105(4), 341–374 (2010)

    MathSciNet  Google Scholar 

  42. Rosa J.L., Robin A., Silva M.B., Baldan C.A., Peres M.P.: Electrodeposition of copper on titanium wires: Taguchi experimental design approach. J. Mater. Process. Technol. 209(3), 1181–1188 (2009)

    Article  Google Scholar 

  43. Pan Q.K., Wang L., Qian B.: A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems. Comput. Oper. Res. 36(8), 2498–2511 (2009)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiuping Xu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nie, L., Xu, J. & Tu, Y. Maintenance Scheduling Problem with Fuzzy Random Time Windows on a Single Machine. Arab J Sci Eng 40, 959–974 (2015). https://doi.org/10.1007/s13369-014-1560-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-014-1560-2

Keywords

Navigation