Skip to main content
SpringerLink
Log in

A fuzzy logic-based approach in capacity-planning problems

  • Original Article
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

In capacity-planning systems, various sources of uncertainty and imprecision are encountered. In most cases, the uncertainty is determined by the subjective beliefs of managers linguistically. However, the measurement of mangers’ judgments is difficult and vague. Therefore, a fuzzy logic-based approach is proposed to deal with capacity-planning problems in the presence of the uncertain demand, set-up resources, and the capacity constraints. Firstly, fuzzy numbers are used to represent uncertain data. Secondly, fuzzy if-then rules are employed to model vaguely defined relations between fuzzy numbers. Then, the computational aspects of fuzzy models and interpretations of inference results are illustrated by a numerical case. Finally, three examples are used to verify the proposed representation and inference mechanism.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Yao J-S, Chang S-C, Su J-S (2000) Fuzzy inventory without backorder for fuzzy order quantity and fuzzy total demand quantity. Comput Oper Res 27:935–962

    Article  Google Scholar 

  2. Yao J-S, Lee H-M (1999) Fuzzy inventory with or without backorder for fuzzy order quantity with trapezoid fuzzy number. Fuzzy Sets Syst 105:311–337

    Article  Google Scholar 

  3. Lee H-M, Yao J-S (1998) Economic production quantity for fuzzy demand quantity and fuzzy production quantity. Eur J Oper Res 109:203–211

    Article  Google Scholar 

  4. Chang S-C (1999) Fuzzy production inventory for fuzzy product quantity with triangular fuzzy number. Fuzzy Sets Syst 107:37–57

    Article  Google Scholar 

  5. Chen S-H, Wang C-C, Ramer A (1996) Backorder fuzzy inventory model under function principle. Inf Sci 95:71–79

    Google Scholar 

  6. Vujosevic M, Petrovic D, Petrovic R (1996) EOQ formula when inventory cost is fuzzy. Int J Prod Econ 45:499–504

    Article  Google Scholar 

  7. Yao J-S, Lee H-M (1996) Fuzzy inventory with backorder for fuzzy order quantity. Inf Sci 93:283–319

    Article  Google Scholar 

  8. Pappis CP, Karacapilidis NI (1995) Lot size scheduling using fuzzy numbers. Int Trans Opl Res 2:205–212

    Article  Google Scholar 

  9. Lee YY, Kramer BA, Hwang CL (1991) A comparative study of three lot-sizing methods for the case of fuzzy demand. Int J Oper Prod Manage 11:72–80

    Google Scholar 

  10. Lee YY, Kramer BA, Hwang CL (1990) Part-period balancing with uncertainty: a fuzzy sets theory approach. Int J Oper Prod Manage 1771–1778

  11. McCahon CS, Lee ES (1992) Fuzzy job sequencing for a flow shop. Eur J Oper Res 62:294–301

    Article  Google Scholar 

  12. Ishii H, Konno T (1998) A stochastic inventory problem with fuzzy shortage cost. Eur J Oper Res 106:90–94

    Article  Google Scholar 

  13. Klir GJ, Yuan B (1995) Fuzzy sets and fuzzy logic theory and applications, Prentice Hall, Englewood Cliffs

  14. Petrovic D, Sweeney E (1994) Fuzzy knowledge-based approach to treating uncertainty in inventory control. Comput Integr Manuf Syst 7:147–152

    Article  Google Scholar 

  15. Petrovic D, Petrovic R, Vujosevic M (1996) Fuzzy models for the newsboy problem. Int J Prod Econ 45:435–441

    Article  Google Scholar 

  16. Roy TK, Mait M (1997) A fuzzy EOQ model with demand-dependent unit cost under limited storage capacity. Eur J Oper Res 99:425–43

    Article  Google Scholar 

Download references

Acknowledgement

This research was conducted with the support of National Science Council (NSC 91-2213-E-212-003).

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Da-Yeh University, 112 Shan-Jiau Rd. Da-Tsuen, Chung-Hwa 515, Taiwan ROC

    P.-F. Pai, S.-S. Wang & K.-P. Lin

  2. Department of Industrial Engineering and Enterprise Information, Tung-Hai University, Taichung, Taiwan ROC

    P.-T. Chang

Authors
  1. P.-F. Pai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P.-T. Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S.-S. Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. K.-P. Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P.-F. Pai.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pai, PF., Chang, PT., Wang, SS. et al. A fuzzy logic-based approach in capacity-planning problems. Int J Adv Manuf Technol 23, 806–811 (2004). https://doi.org/10.1007/s00170-003-1640-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-003-1640-z

Keywords

Search

Navigation