Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ L q ∗ q-Rung Orthopair Multi-fuzzy Soft Set
Abstract Location selection is a critical process in decision-making for projects that involve multiple criteria, such as urban planning, industrial site development, or green building projects. Multiple criteria decision making (MCDM) is a systematic approach that evaluates and ranks potential alte...
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Springer
2025-03-01
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| Series: | International Journal of Computational Intelligence Systems |
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| Online Access: | https://doi.org/10.1007/s44196-025-00755-1 |
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| author | Vimala Jayakumar Mahalakshmi Pethaperumal Nasreen Kausar Dragan Pamucar Vladimir Simic Mohammed Abdullah Salman |
| author_facet | Vimala Jayakumar Mahalakshmi Pethaperumal Nasreen Kausar Dragan Pamucar Vladimir Simic Mohammed Abdullah Salman |
| author_sort | Vimala Jayakumar |
| collection | DOAJ |
| description | Abstract Location selection is a critical process in decision-making for projects that involve multiple criteria, such as urban planning, industrial site development, or green building projects. Multiple criteria decision making (MCDM) is a systematic approach that evaluates and ranks potential alternatives based on a set of often conflicting criteria. This study focuses on selecting the optimal urban location for a green building project by employing the $$L_{q}*$$ L q ∗ q-rung orthopair multi-fuzzy soft-MCDM( $$L_{q}*$$ L q ∗ q-ROMFS) techniques. The $$L_{q}*$$ L q ∗ q-ROMFS set combines elements from two distinct theories with lattice ordering parameters: q-rung orthopair fuzzy set and multi-fuzzy soft set. It provides a mathematical framework with multiple parameters that effectively represents problems involving multi-dimensional data within a dataset. We expand this concept by establishing the algebraic structures of $$L_{q}*$$ L q ∗ q-ROMFS sets, including properties like modularity and distributivity, while also analyzing their homomorphism under lattice mappings. Finally, leveraging the $$L_{q}*$$ L q ∗ q-ROMFS matrix, we propose both a choice matrix and a weighted choice matrix to effectively address the selection of the optimal urban location for a green building project. |
| format | Article |
| id | doaj-art-8236bf6d86e248208cfc40dede05466c |
| institution | DOAJ |
| issn | 1875-6883 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj-art-8236bf6d86e248208cfc40dede05466c2025-08-20T03:05:49ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832025-03-0118112710.1007/s44196-025-00755-1Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ L q ∗ q-Rung Orthopair Multi-fuzzy Soft SetVimala Jayakumar0Mahalakshmi Pethaperumal1Nasreen Kausar2Dragan Pamucar3Vladimir Simic4Mohammed Abdullah Salman5Department of Mathematics, Alagappa UniversityDepartment of Mathematics, Alagappa UniversityDepartment of Mathematics, Faculty of Arts and Science, Balıkesir UniversityDepartment of Operations Research and Statistics, Faculty of Organizational Sciences, University of BelgradeFaculty of Transport and Traffic Engineering, University of BelgradeDepartment of Mathematics, Arman UniversityAbstract Location selection is a critical process in decision-making for projects that involve multiple criteria, such as urban planning, industrial site development, or green building projects. Multiple criteria decision making (MCDM) is a systematic approach that evaluates and ranks potential alternatives based on a set of often conflicting criteria. This study focuses on selecting the optimal urban location for a green building project by employing the $$L_{q}*$$ L q ∗ q-rung orthopair multi-fuzzy soft-MCDM( $$L_{q}*$$ L q ∗ q-ROMFS) techniques. The $$L_{q}*$$ L q ∗ q-ROMFS set combines elements from two distinct theories with lattice ordering parameters: q-rung orthopair fuzzy set and multi-fuzzy soft set. It provides a mathematical framework with multiple parameters that effectively represents problems involving multi-dimensional data within a dataset. We expand this concept by establishing the algebraic structures of $$L_{q}*$$ L q ∗ q-ROMFS sets, including properties like modularity and distributivity, while also analyzing their homomorphism under lattice mappings. Finally, leveraging the $$L_{q}*$$ L q ∗ q-ROMFS matrix, we propose both a choice matrix and a weighted choice matrix to effectively address the selection of the optimal urban location for a green building project.https://doi.org/10.1007/s44196-025-00755-1$$L_{q}*$$ L q ∗ q-ROMFS-MCDMGreen building projectModularityDistributivityHomomorphismChoice matrix |
| spellingShingle | Vimala Jayakumar Mahalakshmi Pethaperumal Nasreen Kausar Dragan Pamucar Vladimir Simic Mohammed Abdullah Salman Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ L q ∗ q-Rung Orthopair Multi-fuzzy Soft Set International Journal of Computational Intelligence Systems $$L_{q}*$$ L q ∗ q-ROMFS-MCDM Green building project Modularity Distributivity Homomorphism Choice matrix |
| title | Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ L q ∗ q-Rung Orthopair Multi-fuzzy Soft Set |
| title_full | Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ L q ∗ q-Rung Orthopair Multi-fuzzy Soft Set |
| title_fullStr | Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ L q ∗ q-Rung Orthopair Multi-fuzzy Soft Set |
| title_full_unstemmed | Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ L q ∗ q-Rung Orthopair Multi-fuzzy Soft Set |
| title_short | Lattice-Based Decision Models for Green Urban Development: Insights from $$L_{q}*$$ L q ∗ q-Rung Orthopair Multi-fuzzy Soft Set |
| title_sort | lattice based decision models for green urban development insights from l q l q ∗ q rung orthopair multi fuzzy soft set |
| topic | $$L_{q}*$$ L q ∗ q-ROMFS-MCDM Green building project Modularity Distributivity Homomorphism Choice matrix |
| url | https://doi.org/10.1007/s44196-025-00755-1 |
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