Skip to main content
Log in

An aspect of bilevel interval linear fractional transportation problem with disparate flows: a fuzzy programming approach

  • ORIGINAL ARTICLE
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

In present times, the e-commerce industry has become a crucial platform between the manufacturers and the common man. There might arise some situations in the market due to which manufacturers are not able to estimate the exact demand for their products, which may result in excess production. Moreover, the demand for the products in the market depends on the purchasing power of the common man. The decrease in purchasing power results in the low sale of the products. This uncertain situation of the market has been depicted by Bilevel Interval Linear Fractional Transportation Problem with distinct flows. The supply, demand, and cost coefficients in the objective functions at two levels are interval parameters. The two-level problem comprises of delivery of products from manufacturers to e-warehouses at the upper level and then to customers at the lower level. At upper level, flow is enhanced since the goods which are manufactured by the industries in large quantities need to be sold out. At lower level, flow is restricted while transporting the goods from e-warehouses to customers. Further, in order to promote the sale of the products, e-websites offer the customers free delivery of the products at their doorsteps. At the same time, they also pick the goods from them if the products are damaged or not of their choice or for any other reason. This in turn incurs the additional cost to the e-websites. The constraints in this defined problem are mixed. The interval parameters in the defined problem are tackled using the concept of centre and width of the interval. This converts the bilevel problem into a bilevel multi-objective transportation problem. A satisfactory solution to the problem is obtained by the fuzzy programming and goal programming approaches. A numerical is illustrated explaining the methodology. Further, the solutions are compared through these two techniques.

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

Data availability

The data used in this paper does not relate to any industry/organization from the real world.

References

Download references

Acknowledgements

The authors would like to thank the Institution of Eminence (IOE), University of Delhi for supporting this research. (Vide Grant No. IOE/2021/12/FRP). The authors are also grateful to the reviewers for their valuable suggestions, incorporating which has helped us in improving the quality of the paper to a great extent.

Funding

This study was supported by the Institution of Eminence (IOE), University of Delhi (Vide Grant No. IOE/2021/12/FRP).

Author information

Authors and Affiliations

Authors

Contributions

Both the authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [CKJ] and [RA]. The first draft of the manuscript was written by [RA] and both the authors commented on previous versions of the manuscript. Both the authors read and approved the final manuscript.

Corresponding author

Correspondence to Chandra K. Jaggi.

Ethics declarations

Conflict of interest

There is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Arora, R., Jaggi, C.K. An aspect of bilevel interval linear fractional transportation problem with disparate flows: a fuzzy programming approach. Int J Syst Assur Eng Manag 14, 2276–2288 (2023). https://doi.org/10.1007/s13198-023-02069-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-023-02069-x

Keywords

Mathematics Subject Classification

JEL Classification

Navigation