Multiobjective optimization problems have a significant role in modeling and optimizing the framework of different real-life issues. It may not always be possible to obtain a single solution that satisfies each objective efficiently; however, there is ample opportunity to get a compromise solution to multiobjective programming problems (MOPPs). Neutrosophic set (NS) is the extension of fuzzy and intuitionistic fuzzy sets. Thus, based on NS, this study presents neutrosophic optimization models for MOPP under the neutrosophic fuzzy environment. We have developed three models while keeping in mind the maximal satisfactory degree of decision-maker(s). The proposed models are then applied to various discussed numerical examples, and solution results are compared with other approaches. Also, the propounded models are implemented in the pharmaceutical supply chain planning problem. The sensitivity analysis of the obtained outcomes at different criteria has been performed. At last, the conclusion and future research scope have been depicted effectively.
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All authors are very thankful to the Editor-in-Chief, anonymous Guest Editor, and potential reviewers for providing in-depth comments and suggestions that improved the readability and clarity of the manuscript.
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Ahmad, F. Interactive neutrosophic optimization technique for multiobjective programming problems: an application to pharmaceutical supply chain management. Ann Oper Res (2021). https://doi.org/10.1007/s10479-021-03997-2
- Intuitionistic fuzzy parameters
- Neutrosophic optimization methods
- Multiobjective programming problem
- Pharmaceutical supply chain management