Open Access
Issue
RAIRO-Oper. Res.
Volume 58, Number 6, November-December 2024
Page(s) 4927 - 4954
DOI https://doi.org/10.1051/ro/2024135
Published online 21 November 2024
  • J.R. Artalejo, A note on the optimality of the N-and D-policies for the M/G/1 queue. Oper. Res. Lett. 30 (2002) 375–376. [CrossRef] [MathSciNet] [Google Scholar]
  • B. Bank and S.K. Samanta, Analytical and computational studies of the BMAP/G(a,Y)/1 queue. Commun. Stat. Theory Methods 50 (2021) 3586–3614. [CrossRef] [Google Scholar]
  • A. Begum and G. Choudhury, Analysis of a bulk arrival N-policy queue with two-service genre, breakdown, delayed repair under Bernoulli vacation and repeated service policy. RAIRO Oper. Res. 56 (2022) 979–1012. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • D. Bini and B. Meini, On the solution of a nonlinear matrix equation arising in queueing problems. SIAM J. Matrix Anal. Appl. 17(4) (1996) 906–926. [CrossRef] [MathSciNet] [Google Scholar]
  • Y.C. Chang and W.L. Pearn, Optimal management for infinite capacity N-policy M/G/1 queue with a removable service station. Int. J. Syst. Sci. 42 (2011) 1075–1083. [CrossRef] [Google Scholar]
  • G. Choudhury and M. Paul, A batch arrival queue with a second optional service channel under N-policy. Stoch. Anal. Appl. 24 (2006) 1–21. [CrossRef] [MathSciNet] [Google Scholar]
  • H.R. Gail, S.L. Hantler and B.A. Taylor, Spectral analysis of M/G/1 and G/M/1 type Markov chains. Adv. Appl. Probab. 28 (1996) 114–165. [CrossRef] [MathSciNet] [Google Scholar]
  • Y. Hao, J. Wang, Z. Wang and M. Yang, Equilibrium joining strategies in the M/M/1 queues with setup times under N-policy. J. Syst. Sci. Syst. Eng. 28 (2019) 141–153. [CrossRef] [Google Scholar]
  • F.C. Jiang, D.C. Huang, C.T. Yang and F. Leu, Lifetime elongation for wireless sensor network using queue-based approaches. J. Supercomput. 59 (2012) 1312–1335. [CrossRef] [Google Scholar]
  • S. Kasahara, T. Takin, Y. Takahashi and T. Hasegawa, MAP/G/1 queue under N-policy with and without vacations. J. Oper. Res. Soc. Jpn. 39 (1996) 188–212. [Google Scholar]
  • C.C. Kuo, K.H. Wang and W.L. Pearn, The interrelationship between N-policy M/G/1/K and F-policy G/M/1/K queues with startup time. Qual. Technol. Quant. Manag. 8 (2011) 237–251. [CrossRef] [Google Scholar]
  • H.W. Lee and N.I. Park, Using factorization for waiting times in BMAP/G/1 queues with N-policy and vacations. Stoch. Anal. Appl. 22 (2004) 755–773. [CrossRef] [Google Scholar]
  • H.W. Lee and K.S. Song, Queue length analysis of MAP/G/1 queue under D-policy. Stoch. Models 20 (2004) 363–380. [CrossRef] [MathSciNet] [Google Scholar]
  • H.W. Lee, S.S. Lee and K.C. Chae, Operating characteristics of MX/G/1 queue with N-policy. Queueing Syst. 15 (1994) 387–399. [CrossRef] [Google Scholar]
  • H.W. Lee, S.S. Lee, J.O. Park and K.C. Chae, Analysis of MX/G/1 queue with N policy and multiple vacations. Appl. Probab. 31 (1994) 467–496. [Google Scholar]
  • H.W. Lee, B.Y. Ahn and N.I. Park, Decompositions of the queue length distributions in the MAP/G/1 queue under multiple and single vacations with N-policy. Stoch. Models 17 (2001) 157–190. [CrossRef] [MathSciNet] [Google Scholar]
  • H.W. Lee, W.J. Seo, S.W. Lee and J. Jeon, Analysis of the MAP/G/1 queue under the min(N, D)-policy. Stoch. Models 26 (2010) 98–123. [CrossRef] [MathSciNet] [Google Scholar]
  • J. Li and L. Liu, On an M/G/1 queue in random environment with Min(N, V) policy. RAIRO Oper. Res. 52 (2018) 61–77. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • Q.L. Li, Z. Lian and L. Liu, An RG-factorization approach for a BMAP/M/1 generalized processor-sharing queue. Stoch. Models 21 (2005) 507–530. [CrossRef] [MathSciNet] [Google Scholar]
  • R. Liu, A.S. Alfa and M. Yu, Analysis of an ND-policy Geo/G/1 queue and its application to wireless sensor networks. Oper. Res. 19 (2019) 449–477. [Google Scholar]
  • D.M. Lucantoni, New results on the single server queue with a batch Markovian arrival process. Stoch. Models 7 (1991) 1–46. [CrossRef] [Google Scholar]
  • D. Nageswari, R. Maheswar and G.R. Kanagachidambaresan, Performance analysis of cluster based homogeneous sensor network using energy efficient N-policy (EENP) model. Clust. Comput. 22 (2019) 12243–12250. [CrossRef] [Google Scholar]
  • R. Nandi, S.K. Samanta and C. Kim, Analysis of D-BMAP/G/1 queue under N-policy. J. Ind. Manag. Optim. 17 (2021) 3603–3631. [CrossRef] [MathSciNet] [Google Scholar]
  • M.F. Neuts, Matrix-geometric Solutions in Stochastic Models: An Algorithmic Approach. Johns Hopkins University Press, Baltimore, Marcel Dekker (1981). [Google Scholar]
  • S. Nishimura, H. Tominaga and T. Shigeta, A computational method for the boundary vector of a BMAP/G/1 queue. J. Oper. Res. Soc. Jpn. 49 (2006) 83–97. [Google Scholar]
  • J.F. Shortle, P.H. Brill, M.J. Fischer, D. Gross and D.M.B. Masi, An algorithm to compute the waiting time distribution for the M/G/1 queue. INFORMS J. Comput. 16 (2004) 152–161. [CrossRef] [MathSciNet] [Google Scholar]
  • C. Sreenivasan, S.R. Chakravarthy and A. Krishnamoorthy, MAP/PH/1 queue with working vacations, vacation interruptions and N policy. Appl. Math. Model. 37 (2013) 3879–3893. [CrossRef] [MathSciNet] [Google Scholar]
  • T.Y. Wang, K.H. Wang and W.L. Pearn, Optimization of the T policy M/G/1 queue with server breakdowns and general startup times. J. Comput. Appl. Math. 228 (2009) 270–278. [CrossRef] [MathSciNet] [Google Scholar]
  • M. Yadin and P. Naor, Queueing systems with a removable service station. J. Oper. Res. Soc. 14 (1963) 393–405. [CrossRef] [Google Scholar]
  • M. Yu and A.S. Alfa, Some analysis results associated with the optimization problem for a discrete-time finite-buffer NT-policy queue. Oper. Res. 16 (2016) 161–179. [Google Scholar]
  • Z.G. Zhang and N. Tian, The N threshold policy for the GI/M/1 queue. Oper. Res. Lett. 32 (2004) 77–84. [CrossRef] [MathSciNet] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.