Ahmad, F and John, B (2022) Modeling and optimization of multiobjective programming problems in neutrosophic hesitant fuzzy environment. In: Soft Computing .
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Abstract
Multiobjective optimization techniques have much importance while solving real-life problems. There may get chances of neutral thoughts and hesitations in real-life problems. This paper has studied the multiobjective programming problems (MOPPs) under neutrosophic hesitant fuzzy uncertainty. The degrees of neutrality and hesitations in MOPPs were introduced, and simultaneously, we have developed the neutrosophic hesitant fuzzy multiobjective programming problems (NHFMOPPs) under a neutrosophic hesitant fuzzy environment. Besides, a new robust solution scheme, namely neutrosophic hesitant fuzzy Pareto optimal solution to the NHFMOPPs, is investigated, and two different optimization techniques are suggested to evaluate it. The validity and applicability of the proposed methods are unanimously implemented on different multiobjective real-life problems. Finally, conclusions, comparative study, and future research direction are addressed based on the presented work. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Item Type: | Journal Article |
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Publication: | Soft Computing |
Publisher: | Springer Science and Business Media Deutschland GmbH |
Additional Information: | The copyright for this article belongs to Springer Science and Business Media Deutschland GmbH |
Keywords: | Computer programming; Membership functions; Pareto principle, Fuzzy membership function; Hesitant fuzzy sets; Indeterminacy hesitant fuzzy membership function; Multi objective; Multiobjective neutrosophic hesitant programming problem; Multiobjective programming problems; Neutrosophic hesitant fuzzy set; Optimality test; Programming problem; Real-life problems, Multiobjective optimization |
Department/Centre: | Division of Interdisciplinary Sciences > Management Studies |
Date Deposited: | 18 May 2022 09:43 |
Last Modified: | 18 May 2022 09:43 |
URI: | https://eprints.iisc.ac.in/id/eprint/71846 |
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