PofoliaShared via Pofolia

Queueing Systems· 2026Q2

Robust queueing for single-server queues with abandonment

Wei You

Short summary

New Robust Queueing (RQ) approximations for mean stationary virtual waiting time in GI/GI/1+GI models with customer abandonment are developed, achieving accuracy via self-consistent fixed-point equations.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Develops Robust Queueing (RQ) approximations for mean stationary virtual waiting time in GI/GI/1+GI models with abandonment.
  • Resolves endogenous dependence of abandonment on waiting times using self-consistent fixed-point equations.
  • Employs deterministic trial approximations for mean and refined surrogates for variance, incorporating heavy-traffic limits.
  • Numerical experiments show the refined approximation is accurate over a broad parameter range.

AI-generated from the title and abstract; the full text is not read.

Abstract

Abstract Single-server queues with customer abandonment arise in call centers and other service systems, yet their steady-state performance is analytically tractable only in special cases. We develop Robust Queueing approximations for the mean stationary virtual waiting time in the $$GI/GI/1{+}GI$$ G I / G I / 1 + G I model. Our starting point is an exact reverse-time representation of the workload in terms of the net-input process, defined as the work brought by customers who eventually enter service minus cumulative service capacity. RQ approximates this random process by its mean plus a robustness parameter times its standard deviation. Abandonment makes both moments endogenous because the probability that a customer enters service depends on the waiting time observed upon arrival. We resolve this dependence by imposing self-consistency through a deterministic trial approximation to the mean stationary virtual waiting time. For the drift, the Poisson compensator identity is exact under Poisson arrivals; under renewal arrivals, the resulting mean Palm correction is controlled on the relevant heavy-traffic optimizer scales. For the variance, we develop a deterministic-time-change surrogate and a refined finite-system surrogate. The refined surrogate heuristically interpolates between two proved variance limits using a scale-dependent variance-reduction factor derived from a heavy-traffic diffusion limit. Both constructions reduce to one-dimensional fixed-point equations that can be solved by bisection using the arrival index of dispersion for counts, the service-time squared coefficient of variation, and the patience distribution. We establish heavy-traffic limits for the $$GI/GI/1{+}GI$$ G I / G I / 1 + G I model and for both RQ fixed points. These limits calibrate the robustness parameter and provide theoretical support for the variance-reduction function. Numerical experiments show that the refined approximation is accurate over a broad parameter range, with short-patience underestimation and residual long-patience errors in some high-variability and tandem models. At fixed subcritical loads, its long-patience limit is the original RQ approximation, whose intermediate-load errors can persist.

The authors' abstract, as published at the source. Queueing Systems, 2026 · DOI ↗

TakeawaysPremium
Ask the paperFree account

Continue with a free account

Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.

Continue free on the web

Sign in with Google or Apple; no card needed. You come back to this paper.

On your phone:

Management Information SystemsBusiness, Management and Accounting