A. Baskar
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
A. Baskar has a total of 1 co-authors. Here are the top co-authors by number of shared publications:
- Mookkaiyah Chandran Saravanarajan
Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India
1 shared publication
Latest Publications
- Open Access
- 19 September 2024
- Published by Universal Wiser Publisher Pte. Ltd in Contemporary Mathematics
- Vol. 5 (3) , 3929-3952
Analyzing an M/G/1 Double Orbit Retrial Queue with the Implementation of a Working Vacation Policy
This paper introduces a double-orbit retrial queue model designed to address patient dissatisfaction by taking into account their willingness to pay for enhanced comfort and service. The system incorporates non-Markovian characteristics and employs a probability-generating function approach to solve its equations. Key performance metrics investigated include expected queue length, system length, and the precision of numerical results derived from empirical data. The model’s application is specifically examined within a hospital management system (HMS), underscoring its relevance in healthcare operations. Overall, the paper offers valuable insights into optimizing design strategies for retrial queue systems featuring unreliable servers, with a focus on enhancing patient satisfaction through personalized service offerings.
- 19 September 2024
- Published by Universal Wiser Publisher Pte. Ltd in Contemporary Mathematics
- Vol. 5 (3) , 3929-3952
Open AccessAnalyzing an M/G/1 Double Orbit Retrial Queue with the Implementation of a Working Vacation Policy
This paper introduces a double-orbit retrial queue model designed to address patient dissatisfaction by taking into account their willingness to pay for enhanced comfort and service. The system incorporates non-Markovian characteristics and employs a probability-generating function approach to solve its equations. Key performance metrics investigated include expected queue length, system length, and the precision of numerical results derived from empirical data. The model’s application is specifically examined within a hospital management system (HMS), underscoring its relevance in healthcare operations. Overall, the paper offers valuable insights into optimizing design strategies for retrial queue systems featuring unreliable servers, with a focus on enhancing patient satisfaction through personalized service offerings.