Article Sidebar

Submitted
July 26, 2022
Published
July 26, 2022
Download
PDF
Statistic
Read Counter : 146 Download : 138

Downloads

Download data is not yet available.

Main Article Content

Abstract

Purpose of the study: A multi-item inventory model for factory outlets in crisp and fuzzy sense are formulated in the fuzzy environment with investment under one constraint has been considered. In this model, demand is constant and is related to the price per unit item. The asteroid fuzzy set is defined and is properties are given.


Methodology: The parameters involved in this model represented by asteroid fuzzy set. The average total cost is defuzzify by ranking method.


Main Findings: The analytical expressions for maximum inventory level and average total cost are derived for the proposed model by using nonlinear programming technique. A numerical example is presented to illustrate the results.


Applications of this study: Ranking Asteroid fuzzy set is considered profitable in small businesses. Here we considered the factory outlet .Also its use is considered to help the small scale entrepreneurs during festival period and pandemic situation.


Novelty/Originality of this study:  In this paper, a novel approach to handle the asteroid fuzzy set is proposed. It uses ranking the cost parameters of the asteroid fuzzy set with the best approximation level. The parameters involved are asteroid fuzzy set and are all ill-defined in nature.

Keywords

Factory Outlets Asteroid Fuzzy Set Multi Items Maximum Investment Ranking Fuzzy Set

Article Details

License

Authors retain the copyright without restrictions for their published content in this journal. IJSRTM is a SHERPA ROMEO Journal. 

Publishing License

This is an open-access article distributed under the terms of  Creative Commons License

 

How to Cite
Maheswari, N., Balasubramanian, K. R., & Parimaladevi, M. (2022). A cost analysis on Multi-item Inventory model for Factory Outlets with investment constraint under ranking Asteroid Fuzzy Set. International Journal of Students’ Research in Technology & Management, 10(3), 12–20. https://doi.org/10.18510/ijsrtm.2022.1033
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
Crossref
Scopus
Google Scholar
Europe PMC

References

  1. Adriana, F., Gabor, Jan-kees van Ommeren, Sleptchenko, A.(2011). An inventory model with discounts for omni channel retailers of slow moving items. European journal of Operations research.
  2. Asma, F., Henry, E.C., Amirthara. (2015). Method for solving fuzzy inventory model with space and investment constraints under robust ranking technique. International Journal of Advanced Research, 3(10), 500 – 504.
  3. Chou, S., Peterson, C., Julian, B., Kuo-Chen, H. (2009). A note on fuzzy inventory model with storage space and budget constraints. Applied Mathematical Modelling, 33(2009), 4069–4077. https://doi.org/10.1016 /j.apm.2009.02.001 DOI: https://doi.org/10.1016/j.apm.2009.02.001
  4. Dhanam, K., Parimaladevi, M.(2016). A displayed inventory model using pentagonal fuzzy number. International Journal of Mathematics and Soft Computing, 6(1), 11-28. https://doi.org/10.26 708/IJMSC.2016.1.6.02 DOI: https://doi.org/10.26708/IJMSC.2016.1.6.02
  5. Hadley, G. & Whitin, T.M. (1958). Analysis of inventory systems Englewood clifs, N J:Printice Hall.
  6. Harries, F.W. (1990). How Many Parts to make at once. Factory, The Magazine of management,10(2), 135-136,152. https://doi.org/10.1287/opre.38.6.947 DOI: https://doi.org/10.1287/opre.38.6.947
  7. Kasthuri, R., Vasanthi, P., Ranganayaki, S., Seshaiah, C. V.(2011). Multi-Item Fuzzy Inventory Model Involving Three Constraints: A Karush-Kuhn-Tucker Conditions Approach. American Journal of Operations Research, 1(2011), 155-159. https://doi.org/10.4236/ajor.2011.13017 DOI: https://doi.org/10.4236/ajor.2011.13017
  8. Mandal, N.K.(2012). Fuzzy economic order quantity model with ranking fuzzy number cost parameters. Yugoslav journal of operations research, 22(1), 247-264. https://doi.org/10.2298/YJOR110727014M DOI: https://doi.org/10.2298/YJOR110727014M
  9. Moghdani, R., Sana, S.S., Zadeh, H.S.(2019). Multi-item fuzzy economic production quantity model with multiple deliveries. Springer-Verlag GmbH Germany, part of Springer Nature. https://doi.org/10.1007/s00500-019-04539-6 DOI: https://doi.org/10.1007/s00500-019-04539-6
  10. Roy, T.K., Maiti, M.(1998). Multi-objective inventory models of deteriorating items with some constraints in a fuzzy environment, Comput. Oper. Res., 25(1998) 1085–1095. https://doi.org/10.1016/S0305-0548(98)00029-X DOI: https://doi.org/10.1016/S0305-0548(98)00029-X
  11. Taft, E.W. (1918). The most economical production lot. Iron Age, 101, 1410-1412.
  12. Zadeh, L.(1965). Fuzzy sets. Information and control, 8(1965), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X DOI: https://doi.org/10.1016/S0019-9958(65)90241-X