The economic improvements of a queueing system with two types of customers achieved by service decomposition are examined. The service process for a Type 2 customer can be split into two phases: a basic service and an additional service. The basic service rate is equal to that of the Type 1 customer. Additional services can be viewed as orders stored in inventory and processed when the server is idle. Once a new customer arrives during idle time, the server will provide a basic service to the customer upon his/her arrival. That is, customers have preemptive priority for orders stored in inventory. We obtain a two-dimensional unbounded Markov process and apply the multivariate generating function to derive the stationary probability of the proposed model as well as some performance measures. The condition under which performing service decomposition can improve economic efficiency is also obtained. Both the optimal inventory capacity and the minimum system cost are obtained numerically. Numerical experiments demonstrate the impact of optimal inventory setting on economic improvement efficiency. Finally, simulation experiments prove the correctness of our theoretical analysis.
Citation: Linhong Li, Wei Xu, Zhen Wang, Liwei Liu. Improving efficiency of the queueing system with two types of customers by service decomposition[J]. AIMS Mathematics, 2023, 8(11): 25382-25408. doi: 10.3934/math.20231295
The economic improvements of a queueing system with two types of customers achieved by service decomposition are examined. The service process for a Type 2 customer can be split into two phases: a basic service and an additional service. The basic service rate is equal to that of the Type 1 customer. Additional services can be viewed as orders stored in inventory and processed when the server is idle. Once a new customer arrives during idle time, the server will provide a basic service to the customer upon his/her arrival. That is, customers have preemptive priority for orders stored in inventory. We obtain a two-dimensional unbounded Markov process and apply the multivariate generating function to derive the stationary probability of the proposed model as well as some performance measures. The condition under which performing service decomposition can improve economic efficiency is also obtained. Both the optimal inventory capacity and the minimum system cost are obtained numerically. Numerical experiments demonstrate the impact of optimal inventory setting on economic improvement efficiency. Finally, simulation experiments prove the correctness of our theoretical analysis.
[1] | A. Marand, H. Li, A. Thorstenson, Joint inventory control and pricing in a service-inventory system, Int. J. Prod. Econ., 209 (2019), 78–91. http://dx.doi.org/10.1016/j.ijpe.2017.07.008 doi: 10.1016/j.ijpe.2017.07.008 |
[2] | G. Hanukov, T. Avinadav, T. Chernonog, U. Spiegel, U. Yechiali, A queueing system with decomposed service and inventoried preliminary services, Appl. Math. Model., 47 (2017), 276–293. http://dx.doi.org/10.1016/j.apm.2017.03.008 doi: 10.1016/j.apm.2017.03.008 |
[3] | G. Hanukov, T. Avinadav, T. Chernonog, U. Yechiali, Performance improvement of a service system via stocking perishable preliminary services, Eur. J. Oper. Res., 274 (2019), 1000–1011. http://dx.doi.org/10.1016/j.ejor.2018.10.027 doi: 10.1016/j.ejor.2018.10.027 |
[4] | G. Hanukov, Improving efficiency of service systems by performing a part of the service without the customer's presence, Eur. J. Oper. Res., 302 (2022), 606–620. http://dx.doi.org/10.1016/j.ejor.2022.01.045 doi: 10.1016/j.ejor.2022.01.045 |
[5] | Wasted time at work costing companies billions in 2006, Salary.com Staff, 2012. Available form: http://www.salary.com/wasted-time-at-work-still-costing-companies-billions-in-2006/. |
[6] | B. Doshi, Queueing systems with vacations-a survey, Queueing Syst., 1 (1986), 29–66. http://dx.doi.org/10.1007/BF01149327 doi: 10.1007/BF01149327 |
[7] | J. Ke, The optimal control of an M/G/1 queueing system with server startup and two vacation types, Appl. Math. Model., 27 (2003), 437–450. http://dx.doi.org/10.1016/S0307-904X(03)00047-7 doi: 10.1016/S0307-904X(03)00047-7 |
[8] | Y. Zhang, D. Yue, W. Yue, A queueing-inventory system with random order size policy and server vacations, Ann. Oper. Res., 310 (2022), 595–620. http://dx.doi.org/10.1007/s10479-020-03859-3 doi: 10.1007/s10479-020-03859-3 |
[9] | R. Meena, M. Jain, A. Assad, R. Sethi, D. Garg, Performance and cost comparative analysis for M/G/1 repairable machining system with N-policy vacation, Math. Comput. Simulat., 200 (2022), 315–328. http://dx.doi.org/10.1016/j.matcom.2022.04.012 doi: 10.1016/j.matcom.2022.04.012 |
[10] | J. Ke, Modified T vacation policy for an M/G/1 queueing system with an unreliable server and startup, Math. Comput. Model., 41 (2005), 1267–1277. http://dx.doi.org/10.1016/j.mcm.2004.08.009 doi: 10.1016/j.mcm.2004.08.009 |
[11] | P. Vijaya Laxmi, P. Rajesh, T. Kassahun, Analysis of a variant working vacation queue with customer impatience and server breakdowns, International Journal of Operational Research, 40 (2021), 437–459. http://dx.doi.org/10.1504/IJOR.2021.114839 doi: 10.1504/IJOR.2021.114839 |
[12] | J. Li, N. Tian, The M/M/1 queue with working vacations and vacation interruptions, J. Syst. Sci. Syst. Eng., 16 (2007), 121–127. http://dx.doi.org/10.1007/s11518-006-5030-6 doi: 10.1007/s11518-006-5030-6 |
[13] | J. Blanc, P. Waal, P. Nain, D. Towsley, Optimal control of admission to a multiserver queue with two arrival streams, IEEE T. Automat. Contr., 37 (1992), 785–797. http://dx.doi.org/10.1109/9.256332 doi: 10.1109/9.256332 |
[14] | A. Turhan, M. Alanyali, D. Starobinski, Optimal admission control in two-class preemptive loss systems, Oper. Res. Lett., 40 (2012), 510–515. http://dx.doi.org/10.1016/j.orl.2012.08.012 doi: 10.1016/j.orl.2012.08.012 |
[15] | B. Kim, J. Kim, Waiting time distributions in an M/G/1 retrial queue with two classes of customers, Ann. Oper. Res., 252 (2017), 121–134. http://dx.doi.org/10.1007/s10479-015-1979-1 doi: 10.1007/s10479-015-1979-1 |
[16] | G. Hanukov, A queueing-inventory model with skeptical and trusting customers, Ann. Oper. Res., in press. http://dx.doi.org/10.1007/s10479-022-04936-5 |
[17] | G. Lawlor, I'Hôpital's rule for multivariable functions, The American Mathematical Monthly, 127 (2020), 717–725. http://dx.doi.org/10.1080/00029890.2020.1793635 doi: 10.1080/00029890.2020.1793635 |
[18] | J. Cohen, The single server queue, In: North-Holland series in applied mathematics and mechanics, Amsterdam: Elsevier, 1982. |
[19] | M. Neuts, Matrix-geometric solutions in stochastic models: an algorithmic approach, New York: Dover Publications, 1994. |
[20] | G. Latouche, V. Ramaswami, A logarithmic reduction algorithm for quasi-birth-and-death processes, J. Appl. Probab., 30 (1993), 650–674. http://dx.doi.org/10.2307/3214773 doi: 10.2307/3214773 |