Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment

Srikant Gupta, Ahteshamul Haq, Irfan Ali, Biswajit Sarkar

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


Determining the methods for fulfilling the continuously increasing customer expectations and maintaining competitiveness in the market while limiting controllable expenses is challenging. Our study thus identifies inefficiencies in the supply chain network (SCN). The initial goal is to obtain the best allocation order for products from various sources with different destinations in an optimal manner. This study considers two types of decision-makers (DMs) operating at two separate groups of SCN, that is, a bi-level decision-making process. The first-level DM moves first and determines the amounts of the quantity transported to distributors, and the second-level DM then rationally chooses their amounts. First-level decision-makers (FLDMs) aimed at minimizing the total costs of transportation, while second-level decision-makers (SLDM) attempt to simultaneously minimize the total delivery time of the SCN and balance the allocation order between various sources and destinations. This investigation implements fuzzy goal programming (FGP) to solve the multi-objective of SCN in an intuitionistic fuzzy environment. The FGP concept was used to define the fuzzy goals, build linear and nonlinear membership functions, and achieve the compromise solution. A real-life case study was used to illustrate the proposed work. The obtained result shows the optimal quantities transported from the various sources to the various destinations that could enable managers to detect the optimum quantity of the product when hierarchical decision-making involving two levels. A case study then illustrates the application of the proposed work.

Original languageEnglish
Pages (from-to)2119-2139
Number of pages21
JournalComplex and Intelligent Systems
Issue number4
Publication statusPublished - 2021 Aug

Bibliographical note

Funding Information:
All the authors are very thankful to the Editor in Chief and the anonymous reviewers who helped improve the paper’s quality and presentation substantially. The paper has been submitted with the consent of all authors. The paper is the joint effort of all authors. This paper has not been submitted anywhere else for publication.

Publisher Copyright:
© 2021, The Author(s).

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems
  • Engineering (miscellaneous)
  • Computational Mathematics


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