Queue mining for delay prediction in multi-class service processes

Senderovich, Arik; Weidlich, Matthias; Gal, Avigdor; Mandelbaum, Avishai

doi:10.1016/j.is.2015.03.010

Cited by 98 publications

(55 citation statements)

References 26 publications

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“…The former correspond to process-aware predictive monitoring techniques, meaning that there is an assumption that an observed sequence is generated by some process that needs to be uncovered via probabilistic reasoning. The process can be represented via a state transition system [52], a Petri net [38] or a queueing model [41]. In our benchmark, we use implementations provided in [38,52] as such, only making changes in the way the predictions are evaluated, in order to bring it in line with the other methods (cf.…”

Section: Discussionmentioning

confidence: 99%

Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

Verenich

Dumas

Rosa

et al. 2019

ACM Trans. Intell. Syst. Technol.

124

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Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running instances (called cases) of a business process, such as the prediction of the outcome, next activity or remaining cycle time of a given process case. These insights could be used to support operational managers in taking remedial actions as business processes unfold, e.g. shifting resources from one case onto another to ensure this latter is completed on time. A number of methods to tackle the remaining cycle time prediction problem have been proposed in the literature. However, due to differences in their experimental setup, choice of datasets, evaluation measures and baselines, the relative merits of each method remain unclear. This article presents a systematic literature review and taxonomy of methods for remaining time prediction in the context of business processes, as well as a cross-benchmark comparison of 16 such methods based on 16 real-life datasets originating from different industry domains.

show abstract

Section: Discussionmentioning

confidence: 99%

Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

Verenich

Dumas

Rosa

et al. 2019

ACM Trans. Intell. Syst. Technol.

124

View full text Add to dashboard Cite

show abstract

“…Some information systems, such as telecommunication [10] and computing networks [11,12], as well as trunked mobile radio systems and air traffic [13][14][15] are also amenable to the channel description.…”

Section: Introductionmentioning

confidence: 99%

Recurrence dynamics of particulate transport with reversible blockage: From a single channel to a bundle of coupled channels

et al. 2019

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We model a particulate flow of constant velocity through confined geometries, ranging from a single channel to a bundle of Nc identical coupled channels, under conditions of reversible blockage. Quantities of interest include the exiting particle flux (or throughput) and the probability that the bundle is open. For a constant entering flux, the bundle evolves through a transient regime to a steady state. We present analytic solutions for the stationary properties of a single channel with capacity N ≤ 3 and for a bundle of channels each of capacity N = 1. For larger values of N and Nc, the system's steady state behavior is explored by numerical simulation. Depending on the deblocking time, the exiting flux either increases monotonically with intensity or displays a maximum at a finite intensity. For large N we observe an abrupt change from a state with few blockages to one in which the bundle is permanently blocked and the exiting flux is due entirely to the release of blocked particles. We also compare the relative efficiency of coupled and uncoupled bundles. For N = 1 the coupled system is always more efficient, but for N > 1 the behavior is more complex.

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“…Log-normal distributions were introduced instead due to their eligibility in queueing theory, as mentioned in Refs. [38,39,40]. Discrete inter-arrival and service times were calculated in our simulation as described in Appendix A.…”

Section: Floor Configuration and Update Rulementioning

confidence: 99%

Exclusive queueing model including the choice of service windows

Tanaka

Yanagisawa

Nishinari

2018

Physica A: Statistical Mechanics and its Applications

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In a queueing system involving multiple service windows, choice behavior is a significant concern. This paper incorporates the choice of service windows into a queueing model with a floor represented by discrete cells.We contrived a logit-based choice algorithm for agents considering the numbers of agents and the distances to all service windows. Simulations were conducted with various parameters of agent choice preference for these two elements and for different floor configurations, including the floor length and the number of service windows. We investigated the model from the viewpoint of transit times and entrance block rates.The influences of the parameters on these factors were surveyed in detail and we determined that there are optimum floor lengths that minimize the transit times. In addition, we observed that the transit times were determined almost entirely by the entrance block rates. The results of the presented model are relevant to understanding queueing systems including the choice of service windows and can be employed to optimize facility design and floor management.

show abstract

Queue mining for delay prediction in multi-class service processes

Cited by 98 publications

References 26 publications

Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring

Recurrence dynamics of particulate transport with reversible blockage: From a single channel to a bundle of coupled channels

Exclusive queueing model including the choice of service windows

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