Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times
As queueing theory and modeling deal with queue length, waiting time and busy period, that all affect costs for an in institution and/or a busing corporation, the optimization plays a crucial role in such models. This paper focuses on the performance modeling and optimal configuration of a single-se...
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Ram Arti Publishers
2025-08-01
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| Series: | International Journal of Mathematical, Engineering and Management Sciences |
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| Online Access: | https://www.ijmems.in/cms/storage/app/public/uploads/volumes/45-IJMEMS-24-0480-10-4-931-964-2025.pdf |
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| author | N. Micheal Mathavavisakan K. Indhira Aliakbar Montazer Haghighi |
| author_facet | N. Micheal Mathavavisakan K. Indhira Aliakbar Montazer Haghighi |
| author_sort | N. Micheal Mathavavisakan |
| collection | DOAJ |
| description | As queueing theory and modeling deal with queue length, waiting time and busy period, that all affect costs for an in institution and/or a busing corporation, the optimization plays a crucial role in such models. This paper focuses on the performance modeling and optimal configuration of a single-server retrial queue with recurrent customers and a standby server, operating under Bernoulli working vacation conditions. The primary aim of the paper is to analyze the dynamics of this queueing model to achieve minimal operational costs while ensuring high performance. Using the supplementary variable technique (SVT), the probability generating functions (PGFs) and steady-state probabilities for the system's states, have been obtained enabling the development of comprehensive performance measures. These measures were rigorously validated through numerical examples. To complement the performance analysis, a cost function was formulated and optimized using advanced techniques, including the grey wolf optimizer (GWO), bat algorithm (BA), whale optimization algorithm (WOA), and cat swarm optimization (CSO). The results revealed that these algorithms successfully minimized operational costs while maintaining optimal system efficiency. |
| format | Article |
| id | doaj-art-9e5b9fb75c774cb29dac6fcc18e096a4 |
| institution | DOAJ |
| issn | 2455-7749 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Ram Arti Publishers |
| record_format | Article |
| series | International Journal of Mathematical, Engineering and Management Sciences |
| spelling | doaj-art-9e5b9fb75c774cb29dac6fcc18e096a42025-08-20T03:18:15ZengRam Arti PublishersInternational Journal of Mathematical, Engineering and Management Sciences2455-77492025-08-01104931964https://doi.org/10.33889/IJMEMS.2025.10.4.045Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial TimesN. Micheal Mathavavisakan0K. Indhira1Aliakbar Montazer Haghighi2Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India.Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India.Department of Mathematics, Prairie View A&M University, Prairie View, Texas, USA.As queueing theory and modeling deal with queue length, waiting time and busy period, that all affect costs for an in institution and/or a busing corporation, the optimization plays a crucial role in such models. This paper focuses on the performance modeling and optimal configuration of a single-server retrial queue with recurrent customers and a standby server, operating under Bernoulli working vacation conditions. The primary aim of the paper is to analyze the dynamics of this queueing model to achieve minimal operational costs while ensuring high performance. Using the supplementary variable technique (SVT), the probability generating functions (PGFs) and steady-state probabilities for the system's states, have been obtained enabling the development of comprehensive performance measures. These measures were rigorously validated through numerical examples. To complement the performance analysis, a cost function was formulated and optimized using advanced techniques, including the grey wolf optimizer (GWO), bat algorithm (BA), whale optimization algorithm (WOA), and cat swarm optimization (CSO). The results revealed that these algorithms successfully minimized operational costs while maintaining optimal system efficiency. https://www.ijmems.in/cms/storage/app/public/uploads/volumes/45-IJMEMS-24-0480-10-4-931-964-2025.pdfrecurrent customerretrial queueworking vacationheuristic optimization |
| spellingShingle | N. Micheal Mathavavisakan K. Indhira Aliakbar Montazer Haghighi Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times International Journal of Mathematical, Engineering and Management Sciences recurrent customer retrial queue working vacation heuristic optimization |
| title | Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times |
| title_full | Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times |
| title_fullStr | Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times |
| title_full_unstemmed | Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times |
| title_short | Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times |
| title_sort | swarm based heuristic optimization of the recurrent customers and standby server under general retrial times |
| topic | recurrent customer retrial queue working vacation heuristic optimization |
| url | https://www.ijmems.in/cms/storage/app/public/uploads/volumes/45-IJMEMS-24-0480-10-4-931-964-2025.pdf |
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