Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks
Abstract Network optimization is accomplished by integrating AI-powered technologies that are industry leading throughout the network lifecycle to optimize network performance in accordance with strategic objectives and maximize return on investment. These technologies utilize live and predictive ne...
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Springer
2025-05-01
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| Series: | International Journal of Computational Intelligence Systems |
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| Online Access: | https://doi.org/10.1007/s44196-025-00868-7 |
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| author | Dilshad Alghazzawi Misbah Hayat Ghaliah Alhamzi Abdul Wakil Baidar |
| author_facet | Dilshad Alghazzawi Misbah Hayat Ghaliah Alhamzi Abdul Wakil Baidar |
| author_sort | Dilshad Alghazzawi |
| collection | DOAJ |
| description | Abstract Network optimization is accomplished by integrating AI-powered technologies that are industry leading throughout the network lifecycle to optimize network performance in accordance with strategic objectives and maximize return on investment. These technologies utilize live and predictive network data to advance the network to its full potential, proactively resolving performance issues prior to the impact on subscribers. By employing predictive forecasting and active monitoring, these systems also assess future interconnection requirements and determine the optimal time and location to increase capacity to achieve the highest possible return, months in advance. This yields a network that is consistently operational and provides exceptional performance, customized to the strategic business objectives, and prepared to satisfy the growing performance requirements of future 5G use cases. Linguistic intuitionistic fuzzy sets (LIFSs) offer an adequate base to represent and manage unpredictability linked to intuitionistic assessments and linguistic structures. Aggregation operators (AOs) play a critical role in enhancing the decision-making (DM) procedure by adeptly managing preferences and uncertainties in multiple attribute decision-making (MADM) problems. This leads to decisions that are both more accurate and reliable. Dynamic AOs, which adjust to time-varying data, further improve flexibility and precision in DM. This research builds upon these concepts to develop novel AOs, including the LIF dynamic Dombi weighted averaging operator (LIFDyDWA), and the LIF dynamic Dombi weighted geometric operator (LIFDyDWG), and illustrates their key structural properties. An algorithm is also proposed to address the challenges of handling imprecise data in DM using the LIF dynamic Dombi aggregation approaches. These strategies are successfully applied to present a solution to an MADM problem concerning the selection of an optimal strategy to enhance the efficiency of telecommunication network systems to demonstrate their effectiveness and superiority. A comparative analysis is provided to validate the efficacy and advantages of the suggested methods over existing approaches. |
| format | Article |
| id | doaj-art-e3f1722f600344119ca1f2149e2bc07b |
| institution | DOAJ |
| issn | 1875-6883 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj-art-e3f1722f600344119ca1f2149e2bc07b2025-08-20T03:16:34ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832025-05-0118112910.1007/s44196-025-00868-7Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication NetworksDilshad Alghazzawi0Misbah Hayat1Ghaliah Alhamzi2Abdul Wakil Baidar3Department of Mathematics, College of Science and Arts, King Abdul Aziz UniversityDepartment of Mathematics, Government College UniversityDepartment of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU)Department of Mathematics, Kabul UniversityAbstract Network optimization is accomplished by integrating AI-powered technologies that are industry leading throughout the network lifecycle to optimize network performance in accordance with strategic objectives and maximize return on investment. These technologies utilize live and predictive network data to advance the network to its full potential, proactively resolving performance issues prior to the impact on subscribers. By employing predictive forecasting and active monitoring, these systems also assess future interconnection requirements and determine the optimal time and location to increase capacity to achieve the highest possible return, months in advance. This yields a network that is consistently operational and provides exceptional performance, customized to the strategic business objectives, and prepared to satisfy the growing performance requirements of future 5G use cases. Linguistic intuitionistic fuzzy sets (LIFSs) offer an adequate base to represent and manage unpredictability linked to intuitionistic assessments and linguistic structures. Aggregation operators (AOs) play a critical role in enhancing the decision-making (DM) procedure by adeptly managing preferences and uncertainties in multiple attribute decision-making (MADM) problems. This leads to decisions that are both more accurate and reliable. Dynamic AOs, which adjust to time-varying data, further improve flexibility and precision in DM. This research builds upon these concepts to develop novel AOs, including the LIF dynamic Dombi weighted averaging operator (LIFDyDWA), and the LIF dynamic Dombi weighted geometric operator (LIFDyDWG), and illustrates their key structural properties. An algorithm is also proposed to address the challenges of handling imprecise data in DM using the LIF dynamic Dombi aggregation approaches. These strategies are successfully applied to present a solution to an MADM problem concerning the selection of an optimal strategy to enhance the efficiency of telecommunication network systems to demonstrate their effectiveness and superiority. A comparative analysis is provided to validate the efficacy and advantages of the suggested methods over existing approaches.https://doi.org/10.1007/s44196-025-00868-7Dynamic aggregation operatorsLinguistic intuitionistic fuzzy setMultiple attribute decision-makingTelecommunication network optimization |
| spellingShingle | Dilshad Alghazzawi Misbah Hayat Ghaliah Alhamzi Abdul Wakil Baidar Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks International Journal of Computational Intelligence Systems Dynamic aggregation operators Linguistic intuitionistic fuzzy set Multiple attribute decision-making Telecommunication network optimization |
| title | Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks |
| title_full | Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks |
| title_fullStr | Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks |
| title_full_unstemmed | Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks |
| title_short | Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks |
| title_sort | innovative dombi aggregation operators in linguistic intuitionistic fuzzy environments for optimizing telecommunication networks |
| topic | Dynamic aggregation operators Linguistic intuitionistic fuzzy set Multiple attribute decision-making Telecommunication network optimization |
| url | https://doi.org/10.1007/s44196-025-00868-7 |
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