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Strategic dynamic jockeying between two parallel queues. (English) Zbl 1370.90086

Summary: Consider a two-station, heterogeneous parallel queueing system in which each station operates as an independent \(M/M/1\) queue with its own infinite-capacity buffer. The input to the system is a Poisson process that splits among the two stations according to a Bernoulli splitting mechanism. However, upon arrival, a strategic customer initially joins one of the queues selectively and decides at subsequent arrival and departure epochs whether to jockey (or switch queues) with the aim of reducing her own Sojourn time. There is a holding cost per unit time, and jockeying incurs a fixed non-negative cost while placing the customer at the end of the other queue. We examine individually optimal joining and jockeying policies that minimize the strategic customer’s total expected discounted (or undiscounted) costs over finite and infinite time horizons. The main results reveal that, if the strategic customer is in station 1 with customers in front of her, and \(q_{1}\) and \(q_{2}\) customers in stations 1 and 2, respectively (excluding herself), then the incentive to jockey increases as either increases or \(q_{2}\) decreases. Numerical examples reveal that it may not be optimal to join, and/or jockey to, the station with the shortest queue or the fastest server.

MSC:

90B22 Queues and service in operations research
60K25 Queueing theory (aspects of probability theory)
90C40 Markov and semi-Markov decision processes
Full Text: DOI

References:

[1] 1.AdanI.J.B.F., WesselsJ. & ZijmW.H.M. (1993). Matrix-geometric analysis of the shortest queue problem with threshold jockeying. Operations Research Letters13: 107-112.10.1016/0167-6377(93)90037-H · Zbl 0771.60071 · doi:10.1016/0167-6377(93)90037-H
[2] 2.DisneyR.L. & MitchellW.E. (1970). A solution for queues with instantaneous jockeying and other customer selection rules. Naval Research Logistics Quarterly17(3): 315-325.10.1002/nav.3800170308 · Zbl 0233.60084 · doi:10.1002/nav.3800170308
[3] 3.DownD.G. & LewisM.E. (2006). Dynamic load balancing in parallel queueing systems: Stability and optimal control. European Journal of Operational Research168(2): 509-519.10.1016/j.ejor.2004.04.041 · Zbl 1101.90017 · doi:10.1016/j.ejor.2004.04.041
[4] 4.ElsayedE.A. & BastaniA. (1985). General solutions of the jockeying problem. European Journal of Operational Research22(3): 387-396.10.1016/0377-2217(85)90258-9 · Zbl 0573.60089 · doi:10.1016/0377-2217(85)90258-9
[5] 5.GertsbakhI. (1984). The shorter queue problem: A numerical study using matrix-geometric solution. European Journal of Operational Research15: 374-381.10.1016/0377-2217(84)90106-1 · Zbl 0546.90036 · doi:10.1016/0377-2217(84)90106-1
[6] 6.GlazerA. & HassinR. (1983). Search among queues. Technical Report 406. Institute for Mathematical Studies in the Social Sciences, Stanford University, Palo Alto, CA. · Zbl 0603.60088
[7] 7.HaightF.A. (1958). Two queues in parallel. Biometrika45(3/4): 401-410.10.1093/biomet/45.3-4.4010100304 · Zbl 0086.33801 · doi:10.1093/biomet/45.3-4.401
[8] 8.HassinR. & HavivM. (1994). Equilibrium strategies and the value of information in a two line queueing system with threshold jockeying. Communications in Statistics: Stochastic Models10(2): 415-435. · Zbl 0793.60101
[9] 9.HassinR. & HavivM. (2003). To queue or not to queue: Equilibrium behavior in queueing systems. Boston, MA: Kluwer Academic. · Zbl 1064.60002
[10] 10.HlynkaM., StanfordD.A., PoonW.H. & WangT. (1994). Observing queues before joining. Operations Research42(2): 365-371.10.1287/opre.42.2.365 · Zbl 0805.90046 · doi:10.1287/opre.42.2.365
[11] 11.KaoE.P.C. & LinC. (1990). A matrix-geometric solution of the jockeying problem. European Journal of Operational Research44(1): 67-74.10.1016/0377-2217(90)90315-3 · Zbl 0689.60085 · doi:10.1016/0377-2217(90)90315-3
[12] 12.KingmanJ.F.C. (1961). Two similar queues in parallel. Annals of Mathematical Statistics32: 1314-1323.10.1214/aoms/1177704869 · Zbl 0104.36901 · doi:10.1214/aoms/1177704869
[13] 13.KoenigsbergE. (1966). On jockeying in queues. Management Science12(5): 412-436.10.1287/mnsc.12.5.412 · Zbl 0134.35103 · doi:10.1287/mnsc.12.5.412
[14] 14.LippmanS.A. & StidhamS. (1977). Individual versus social optimization in exponential congestion systems. Operations Research25(2): 233-247.10.1287/opre.25.2.233 · Zbl 0369.90079 · doi:10.1287/opre.25.2.233
[15] 15.MandelbaumA. & YechialiU. (1983). Optimal entering rules for a customer with wait option at an M/G/1 queue. Management Science29(2): 174-187.10.1287/mnsc.29.2.174 · Zbl 0532.90035 · doi:10.1287/mnsc.29.2.174
[16] 16.RossS.M. (1983). Introduction to stochastic dynamic programming. New York, NY: Academic Press, Inc. · Zbl 0567.90065
[17] 17.TarabiaA.M.K. (2008). Analysis of two queues in parallel with jockeying and restricted capacities. Applied Mathematical Modelling32(5): 802-810.10.1016/j.apm.2007.02.014 · Zbl 1165.90409 · doi:10.1016/j.apm.2007.02.014
[18] 18.WeberR.R. (1978). On the optimal assignment of customers to parallel servers. Journal of Applied Probability15(2): 406-413.10.2307/3213411 · Zbl 0378.60095 · doi:10.2307/3213411
[19] 19.WhittW.O. (1986). Deciding which queue to join: Some counterexamples. Operations Research34(1): 55-62.10.1287/opre.34.1.55 · Zbl 0622.90035
[20] 20.XuS.H. & ZhaoY.Q. (1996). Dynamic routing and jockeying controls in a two-station queueing system. Advances in Applied Probability28(4): 1201-1226.10.2307/1428170 · Zbl 0867.90057 · doi:10.2307/1428170
[21] 21.ZhaoY. & GrassmannW.K. (1990). The shortest queue model with jockeying. Naval Research Logistics37(5): 773-787.10.1002/1520-6750(199010)37:5<773::AID-NAV3220370514>3.0.CO;2-2 · Zbl 0706.60092 · doi:10.1002/1520-6750(199010)37:5<773::AID-NAV3220370514>3.0.CO;2-2
[22] 22.ZhaoY. & GrassmannW.K. (1995). Queueing analysis of a jockeying model. Operations Research43(3): 520-529.10.1287/opre.43.3.520 · Zbl 0839.90048 · doi:10.1287/opre.43.3.520
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