4 citations · 6 across the 8 of their papers we have counts for
10 papers
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…
An Unconstrained Optimization Approach to Moment Fitting with Phase Type Distributions
Eliran Sherzer, Yehezkel Resheff, Miklos Telek
Phase type (PH) distributions are widely used in modeling and simulation due to their generality and analytical properties. In such settings, it is often necessary to construct a P…
Analyzing homogenous and heterogeneous multi-server queues via neural networks
Eliran Sherzer
In this paper, we use a machine learning approach to predict the stationary distributions of the number of customers in a single-staiton multi server system. We consider two system…
Computing the steady-state probabilities of a tandem queueing system, a Machine Learning approach
Eliran Sherzer
Tandem queueing networks are widely used to model systems where services are provided in sequential stages. In this study, we assume that each station in the tandem system operates…
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…
Learning policies for resource allocation in business processes
J. Middelhuis, R. Lo Bianco, E. Scherzer +3
Efficient allocation of resources to activities is pivotal in executing business processes but remains challenging. While resource allocation methodologies are well-established in…
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…
When to arrive at a queue with earliness, tardiness and waiting costs
Eliran Sherzer, Yoav Kerner
We consider a queueing facility where customers decide when to arrive. All customers have the same desired arrival time (w.l.o.g.\ time zero). There is one server, and the service…
Customers' abandonment strategy in an M/G/1 queue
Eliran Sherzer, Yoav Kerner
We consider an M/G/1 queue in which the customers, while waiting in line, may renege from it. We study the Nash equilibrium profile among customers, and show that it is defined by…