Skip to main content
SpringerLink
Log in

An Integrated Production Model in Fuzzy Environment Under Inflation

  • Conference paper
  • First Online:
Proceedings of the Third International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 259))

  • 1481 Accesses

Abstract

In this research article, an integrated system with variable production is developed in fuzzy environment. The demand rate is regarded as an increasing function of time. In developing the proposed model, it is assumed that the manufacturer takes the raw materials in multiple batches from the supplier, process them to produce finished products and deliver to the buyer in multiple shipments. The effect of inflation and time value of money is also taken into consideration. All the cost parameters are considered as triangular fuzzy numbers and signed distance method is used for defuzzification. The model is illustrated with numerical example and sensitivity analysis with respect to the system parameters is also executed.

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. Zadeh, L.A.: Fuzzy sets. Inform. Cont. 8(3), 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  2. Park, K.S.: Inventory models with partial backorders. Int. J. Sys. Sci. 13, 1313–1317 (1982)

    Article  MATH  Google Scholar 

  3. Chang, H.C.: An application of fuzzy sets theory to the EOQ model with imperfect quality items. Comp. Oper. Res. 31, 2079–2092 (2004)

    Article  MATH  Google Scholar 

  4. Singh, S.R., Kumari, R., Kumar, N.: Optimisation of fuzzy inventory model for differential items. Int. J. Oper. Res. 11(3), 290–315 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  5. Yadav, D., Singh, S.R., Kumari, R.: Retailer’s optimal policy under inflation in fuzzy environment with trade credit. Int. J. Sys. Sci. (2013). http://dx.doi.org/10.1080/00207721.2013.801094

  6. Goyal, S.K.: An integrated inventory model for a single supplier-single customer problem. Int. J. Prod. Econ. 15(1), 107–111 (1976)

    Article  Google Scholar 

  7. Banerjee, A.: A joint economic lot size model for purchaser and vendor. Dec. Sci. 17, 292–311 (1986)

    Article  Google Scholar 

  8. Banerjee, A., Kim, S.L.: An integrated JIT inventory model. Int. J. Oper. Prod. Manag. 15, 237–244 (1995)

    Article  Google Scholar 

  9. Kumar, N., Singh, S.R., Kumari, R.: Three-Echelon supply chain inventory model for deteriorating items with limited storage facility and lead-time under inflation. Int. J. Serv. Oper. Manag. 13(1), 98–118 (2012)

    Google Scholar 

  10. Omar, M., Sarker, R., Othman, W.A.M.: A just-in-time three-level integrated manufacturing system for linearly time-varying demand process. App. Math. Mod. 37, 1275–1281 (2013)

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  12. Bierman, H., Thomas, J.: Inventory decisions under inflationary conditions. Dec. Sci. 8, 151–155 (1977)

    Article  Google Scholar 

  13. Yang, H.L., Teng, J.T., Chern, M.S.: Deterministic inventory lot-size models under inflation with shortages and deterioration for fluctuating demand. Nav. Res. Log. 48(2), 144–158 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  14. Singh, S.R., Kumar, N., Kumari, R.: An inventory model for deteriorating items with shortages and stock-dependent demand under inflation for two-shops under one management. Opsearch 47(4), 311–329 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  15. Singh, S.R., Swati, C.C.: An optimizing policy for decaying items with ramp-type demand and preservation technology under trade credit and inflation. Rev. Busi. Tech. Res 5(1), 54–62 (2012)

    Google Scholar 

  16. Singh, S.R., Jain, S., Pareek, S.: A warehouse imperfect fuzzified production model with shortages under inflationary conditions. Adv. Dec. Sci. (2012). doi:10.1155/2012/638060

Download references

Acknowledgments

The second author would like to thank to CSIR (New Delhi) for providing finan-cial help in the form of JRF vide letter no. 08/017(0017)/2011-EMR-I.

Author information

Authors and Affiliations

  1. Department of Mathematics, D. N. College, Meerut, 250001, India

    S. R. Singh & Swati Sharma

Authors
  1. S. R. Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Swati Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. R. Singh .

Editor information

Editors and Affiliations

  1. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

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

    Kusum Deep

  3. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

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

    Jagdish Chand Bansal

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer India

About this paper

Cite this paper

Singh, S.R., Sharma, S. (2014). An Integrated Production Model in Fuzzy Environment Under Inflation. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 259. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1768-8_27

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-1768-8_27

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1767-1

  • Online ISBN: 978-81-322-1768-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation