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Modified EDAS method for MCDM in robotic agrifarming with picture fuzzy soft Dombi aggregation operators

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Abstract

In recent decades, robotics and automation technologies play an emerging role in the area of agriculture development. In the present communication, the concept of digital farming in terms of robotic agrifarming has been considered to be a multi-criteria decision-making problem under conflicting criteria and uncertain information availability. The notion of score/accuracy function of picture fuzzy soft number and picture fuzzy soft Dombi aggregation operators (weighted/ordered weighted average, hybrid/weighted geometric) have been introduced along with various operational laws and properties. Further, for the sake of providing a larger space to the decision makers and including the parametrization feature of the imprecise information, the traditional EDAS (Evaluation Based On Distance from average Solution) methodology has been modified and presented in the light of the proposed score/accuracy function and the introduced Dombi aggregation operators. In addition to this, an illustrative example related to digital farming has been studied in detail showing that the proposed methodology is highly helpful in finding the best alternative in order to have sustainable farming among various types of agrifarming. In order to understand the feasibility, loftiness and dependability of the proposed modified EDAS methodology, the comparative remarks and advantages have been listed for better understanding and readability with some existing MCDM approaches.

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Acknowledgements

We are very much thankful to the Editorial Office and anonymous reviewers for suggesting the points/mistakes which have been well implemented/corrected for the necessary improvement of the manuscript. We sincerely acknowledge our deep sense of gratitude to the Editorial office and reviewers for giving their valuable time to the manuscript.

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The authors declare that the research carried out in this article has no source of funding.

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Authors and Affiliations

  1. Department of Mathematics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, 173 234, India

    Himanshu Dhumras & Rakesh Kumar Bajaj

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  1. Himanshu Dhumras
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  2. Rakesh Kumar Bajaj
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Contributions

HD and RKB equally contributed to the design and implementation of the research, to the analysis of the results, and to the writing of the manuscript.

Corresponding author

Correspondence to Rakesh Kumar Bajaj.

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Dhumras, H., Bajaj, R.K. Modified EDAS method for MCDM in robotic agrifarming with picture fuzzy soft Dombi aggregation operators. Soft Comput 27, 5077–5098 (2023). https://doi.org/10.1007/s00500-023-07927-1

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