4 citations · 6 across the 8 of their papers we have counts for
4 papers · 1 filter
A Learning-Based Superposition Operator for Non-Renewal Arrival Processes in Queueing Networks
Eliran Sherzer
The superposition of arrival processes is a fundamental yet analytically intractable operation in queueing networks when inputs are general non-renewal streams. Classical methods e…
Supervised Learning for the (s,S) Inventory Model with General Interarrival Demands and General Lead Times
Eliran Sherzer, Yonit Barron
The continuous-review (s,S) inventory model is a cornerstone of stochastic inventory theory, yet its analysis becomes analytically intractable when dealing with non-Markovian syste…
Approximating G(t)/GI/1 queues with deep learning
Eliran Sherzer, Opher Baron, Dmitry Krass +1
In this paper, we apply a supervised machine-learning approach to solve a fundamental problem in queueing theory: estimating the transient distribution of the number in the system…
Can machines solve general queueing systems?
Eliran Sherzer, Arik Senderovich, Opher Baron +1
In this paper, we analyze how well a machine can solve a general problem in queueing theory. To answer this question, we use a deep learning model to predict the stationary queue-l…