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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Novel Decision Modeling for Manufacturing Sustainability under Single-Valued Neutrosophic Hesitant Fuzzy Rough
Muhammad Kamran1, Nadeem Salamat1, Shahzaib Ashraf1
1Institute of Mathematics, Khwaja Fareed University of Engineering & Information Technology Rahim, Yar Khan 64200, Punjab, Pakistan.
Computational Intelligence and Neuroscience
|October 16, 2024
Summary
A new multicriteria decision-making method using single-valued neutrosophic hesitant fuzzy rough (SV-NHFR) aggregation operators enhances manufacturing sustainability. This approach addresses uncertainty and optimizes choices for sustainable business practices.
Area of Science:
- Operations Research
- Decision Science
- Sustainable Manufacturing
Background:
- Sustainability is a critical global economic issue, with many businesses facing losses due to neglecting it.
- Modern manufacturing increasingly integrates technologies like AI, IoT, and Big Data Analytics to support long-term viability.
- Identifying and prioritizing factors that promote sustainability adoption is crucial for industrial success.
Purpose of the Study:
- To develop a novel multicriteria decision-making (MCDM) framework for enhancing sustainability in manufacturing.
- To propose new single-valued neutrosophic hesitant fuzzy rough (SV-NHFR) weighted averaging and geometric aggregation operators.
- To provide a method for selecting optimal elements for a sustainable manufacturing sector.
Main Methods:
- Development of novel SV-NHFR weighted averaging and geometric aggregation operators.
- Application of these operators within a multicriteria decision-making framework.
- A case study focusing on sustainable manufacturing element selection.
- Comparative analysis with existing methodologies and validity testing.
Main Results:
- The proposed SV-NHFR aggregation operators effectively address uncertainty in decision-making.
- The developed method demonstrated reliability and validity in a sustainable manufacturing case study.
- The technique offers improved decision adaptability compared to existing methods.
Conclusions:
- The novel SV-NHFR aggregation operators provide a robust tool for sustainable manufacturing decisions.
- The framework supports the integration of advanced technologies for sustainability adoption.
- The method offers a viable solution for overcoming limitations in current decision-making approaches for sustainability.
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