A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation
In recent years, as corporate consciousness of environmental preservation and sustainable growth has increased, the importance of sustainability marketing in the logistic process has grown. Both academics and business have increased their focus on sustainable logistics procedures. As the body of lit...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2023-08-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-1527.pdf |
| _version_ | 1797732194516467712 |
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| author | Muhammad Riaz Hafiz Muhammad Athar Farid Ayesha Razzaq Vladimir Simic |
| author_facet | Muhammad Riaz Hafiz Muhammad Athar Farid Ayesha Razzaq Vladimir Simic |
| author_sort | Muhammad Riaz |
| collection | DOAJ |
| description | In recent years, as corporate consciousness of environmental preservation and sustainable growth has increased, the importance of sustainability marketing in the logistic process has grown. Both academics and business have increased their focus on sustainable logistics procedures. As the body of literature expands, expanding the field’s knowledge requires establishing new avenues by analyzing past research critically and identifying future prospects. The concept of “q-rung orthopair fuzzy soft set” (q-ROFSS) is a new hybrid model of a q-rung orthopair fuzzy set (q-ROFS) and soft set (SS). A q-ROFSS is a novel approach to address uncertain information in terms of generalized membership grades in a broader space. The basic alluring characteristic of q-ROFS is that they provide a broader space for membership and non-membership grades whereas SS is a robust approach to address uncertain information. These models play a vital role in various fields such as decision analysis, information analysis, computational intelligence, and artificial intelligence. The main objective of this article is to construct new aggregation operators (AOs) named “q-rung orthopair fuzzy soft prioritized weighted averaging” (q-ROFSPWA) operator and “q-rung orthopair fuzzy soft prioritized weighted geometric” (q-ROFSPWG) operator for the fusion of a group of q-rung orthopair fuzzy soft numbers and to tackle complexities and difficulties in existing operators. These AOs provide more effective information fusion tools for uncertain multi-attribute decision-making problems. Additionally, it was shown that the proposed AOs have a higher power of discriminating and are less sensitive to noise when it comes to evaluating the performances of sustainable logistic providers. |
| first_indexed | 2024-03-12T12:09:48Z |
| format | Article |
| id | doaj.art-8a275c42113d40c0822182762c3339fa |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-03-12T12:09:48Z |
| publishDate | 2023-08-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-8a275c42113d40c0822182762c3339fa2023-08-30T15:05:14ZengPeerJ Inc.PeerJ Computer Science2376-59922023-08-019e152710.7717/peerj-cs.1527A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregationMuhammad Riaz0Hafiz Muhammad Athar Farid1Ayesha Razzaq2Vladimir Simic3Department of Mathematics, University of the Punjab, Lahore, Punjab, PakistanDepartment of Mathematics, University of the Punjab, Lahore, Punjab, PakistanDepartment of Mathematics, University of the Punjab, Lahore, Punjab, PakistanFaculty of Transport and Traffic Engineering, University of Belgrade, Belgrade, SerbiaIn recent years, as corporate consciousness of environmental preservation and sustainable growth has increased, the importance of sustainability marketing in the logistic process has grown. Both academics and business have increased their focus on sustainable logistics procedures. As the body of literature expands, expanding the field’s knowledge requires establishing new avenues by analyzing past research critically and identifying future prospects. The concept of “q-rung orthopair fuzzy soft set” (q-ROFSS) is a new hybrid model of a q-rung orthopair fuzzy set (q-ROFS) and soft set (SS). A q-ROFSS is a novel approach to address uncertain information in terms of generalized membership grades in a broader space. The basic alluring characteristic of q-ROFS is that they provide a broader space for membership and non-membership grades whereas SS is a robust approach to address uncertain information. These models play a vital role in various fields such as decision analysis, information analysis, computational intelligence, and artificial intelligence. The main objective of this article is to construct new aggregation operators (AOs) named “q-rung orthopair fuzzy soft prioritized weighted averaging” (q-ROFSPWA) operator and “q-rung orthopair fuzzy soft prioritized weighted geometric” (q-ROFSPWG) operator for the fusion of a group of q-rung orthopair fuzzy soft numbers and to tackle complexities and difficulties in existing operators. These AOs provide more effective information fusion tools for uncertain multi-attribute decision-making problems. Additionally, it was shown that the proposed AOs have a higher power of discriminating and are less sensitive to noise when it comes to evaluating the performances of sustainable logistic providers.https://peerj.com/articles/cs-1527.pdfq-rung orthopair fuzzy soft setAggregation operatorsSustainable logistic processesDecison-making |
| spellingShingle | Muhammad Riaz Hafiz Muhammad Athar Farid Ayesha Razzaq Vladimir Simic A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation PeerJ Computer Science q-rung orthopair fuzzy soft set Aggregation operators Sustainable logistic processes Decison-making |
| title | A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation |
| title_full | A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation |
| title_fullStr | A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation |
| title_full_unstemmed | A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation |
| title_short | A new approach to sustainable logistic processes with q-rung orthopair fuzzy soft information aggregation |
| title_sort | new approach to sustainable logistic processes with q rung orthopair fuzzy soft information aggregation |
| topic | q-rung orthopair fuzzy soft set Aggregation operators Sustainable logistic processes Decison-making |
| url | https://peerj.com/articles/cs-1527.pdf |
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