Skip to main content
SpringerLink
Log in

A Fuzzified Production Model with Time Varying Demand Under Shortages and Inflation

  • Conference paper
  • First Online:
Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 236))

  • 1699 Accesses

Abstract

We develop an inventory model with time-dependent demand rate and deterioration, allowing shortages. The production rate is assumed to be finite and proportional to the demand rate. The shortages are partially backlogged with time-dependent rate. Inflation is also taken in this model. Inflation plays a very significant role in inventory policy. We developed the model in both fuzzy and crisp sense. The model is solved logically to obtain the optimal solution of the problem. It is then illustrated with the help of numerical examples. Sensitivity of the optimal solution with respect to changes in the values of the system parameters is also studied.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bierman, H., Thomas, J.: Inventory decisions under inflationary condition. Deci. Sci. 8(1), 151–155 (1977)

    Article  Google Scholar 

  2. Brahmbhatt, A.C.: Economic order quantity under variable rate of inflation and mark-up prices. Productivity 23, 127–130 (1982)

    Google Scholar 

  3. Buzacott, J.A.: Economic order quantities with inflation. Oper. Res. Quart. 26(3), 553–558 (1975)

    Article  MathSciNet  Google Scholar 

  4. Chakrabarti, T., Giri, B.C., Chaudhuri, K.S.: An EOQ model for items weibull distribution deterioration shortages and trended demand: an extension of philip’s model. Comp. Oper. Res. 25, 649–657 (1998)

    Article  Google Scholar 

  5. Chang, H.C., Yao, J.S., Ouyang, L.Y.: Fuzzy mixture inventory model with variable lead-time based on probabilistic fuzzy set and triangular fuzzy number. Math. Comp. Mode. 39(2–3), 287–304 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  6. Chang, H.C., Yao, J.S., Ouyang, L.Y.: Fuzzy mixture inventory model involving fuzzy random variable lead time demand and fuzzy total demand. Euro. J. Oper. Res. 169(1), 65–80 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  7. Chen, S.H., Wang, C.C.: Backorder fuzzy inventory model under functional principle. Inf. Sci. 95, 71–79 (1996)

    Article  Google Scholar 

  8. Covert, R.P., Philip, G.C.: An EOQ model for items with weibull distribution deterioration. AIIE Trans. 5, 323–326 (1973)

    Article  Google Scholar 

  9. Dave, U.: On a discrete-in-time order-level inventory model for deteriorating items. Oper. Res. 30, 349–354 (1979)

    MATH  Google Scholar 

  10. Ghare, P.M., Schrader, S.F.: A model for exponentially decaying inventory. J. Ind. Eng. 14, 238–243 (1963)

    Google Scholar 

  11. Goyal, S.K., Gunasekaran, A.: An integrated production-inventory-marketing model for deteriorating items. Comp. Ind. Eng 28(4), 755–762 (1995)

    Article  Google Scholar 

  12. Goyal, S.K., Giri, B.C.: Recent trends in modeling of deteriorating inventory. Euro. J. Oper. Res. 134, 1–16 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  13. Kang, S., Kim, I.: A study on the price and production level of the deteriorating inventory system. Int. J. Prod. Res. 21, 899–908 (1983)

    Article  MATH  Google Scholar 

  14. Lee, H.M., Yao, J.S.: Economic order quantity in fuzzy sense for inventory without backorder model. Fuzzy Sets Syst. 105, 13–31 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  15. Misra, R.B.: Optimum production lot-size model for a system with deteriorating inventory. Int. J. Prod. Res. 13(5), 495–505 (1975)

    Article  Google Scholar 

  16. Misra, R.B.: A study of inflation effects on inventory system. Logi. Spect. 9(3), 260–268 (1997)

    Google Scholar 

  17. Moon, I., Yun, W.: A note on evaluating inventory systems: a net present value frame work. Eng. Econ. 39(1), 93–99 (1993)

    Article  Google Scholar 

  18. Nayebi, M.A., Sharifi, M., Shahriari, M.R., Zarabadipour, O.: Fuzzy-chance constrained multi-objective programming applications for inventory control model. App. Math. Sci. 6(5), 209–228 (2012)

    MATH  Google Scholar 

  19. Raafat, F.: Survey of literature on continuously deteriorating inventory models. J. Oper. Res. Soci. 42, 27–37 (1991)

    MATH  Google Scholar 

  20. Simmons, D., Cheng, J.: An alternative approach to computing economic run quantity. Int. J. Prod. Res. 56(3), 837–847 (2008)

    Article  Google Scholar 

  21. Singh, S.R., Bhatia, D.: Fuzzy inventory model for non-instantaneous perishable products under inflation. Int. J. Man. Res. Tech. 4(2), 261–270 (2010)

    Google Scholar 

  22. Singh, S.R., Kumar, T., Gupta, C.B.: Optimal replenishment policy for ameliorating item with shortages under inflation and time value of money using genetic algorithm. Int. J. Comp. App. 27(1), 5–17 (2011)

    MathSciNet  Google Scholar 

  23. Teng, J.T., Chang, C.T.: Economic production quantity models for deteriorating itemswith price- and stock-dependent demand. Comp. Oper. Res. 32(2), 297–308 (2005)

    Article  MATH  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  25. Wee, H.M.: Economic production lot-size model for deteriorating items with partial backordering. Comp. Ind. Eng. 20(2), 187–197 (1993)

    Google Scholar 

  26. Wee, H.M., Jong, J.F.: An integrated multi-lot-size production inventory modelfor deteriorating items. Manage. Syst. 5, 97–114 (1998)

    Google Scholar 

  27. Yang, P.C., Wee, H.M.: Economic order policy of deteriorated item for vendor and buyer: an integrated approach. Prod. Plan. Cont. 11, 474–480 (2000)

    Article  Google Scholar 

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

    Article  MATH  Google Scholar 

  29. Zadeh, L.: Fuzzy sets. Inf. control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre of Mathematical Sciences, Banasthali University, Banasthali, Rajasthan, India

    Shalini Jain

  2. Department of Mathematics, D.N. College, Meerut, India

    S. R. Singh

Authors
  1. Shalini Jain
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. R. Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shalini Jain .

Editor information

Editors and Affiliations

  1. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    B. V. Babu

  2. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  3. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

  5. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  6. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Kanad Ray

  7. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Umesh Gupta

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer India

About this paper

Cite this paper

Jain, S., Singh, S.R. (2014). A Fuzzified Production Model with Time Varying Demand Under Shortages and Inflation. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_43

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-1602-5_43

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1601-8

  • Online ISBN: 978-81-322-1602-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation