Program at a Glance

 

Sunday

July 1

Monday

July 2

Tuesday

July 3

Wednesday

July 4

Morning to Afternoon

---

Parallel Sessions

Parallel Sessions

Parallel Sessions

Keynote

---

Sergei Foss:

Heavy Tails

Bert Zwart:

Power Systems

Eli David:

Artificial Intelligence

Evening

---

Tour:

City of David

Tour:

Israel Museum

Tour:*

Jerusalem Walls

Night

Reception
(8:00 pm)

Dinner

Gala Dinner

Dinner*

 

*Not included in registration fees.

Detailed Program

Monday, July 2nd

9:00-10:30

M1


Control of fluid systems 1

Piunovskiy

Mendelson

van der Boor

Queues in use

Hanukuv

Perel

Yechiali

Discrete time systems

Oblakova

Nobel

Verdonck

10:30-11:00 Coffee and Refreshment



11:00-12:30

M2


Batch service systems 1

Baetens

Klünder

Dendievel

Statistics in queues

Nazarathy

Scheinhardt

Ravner

Strategic behavior and control 1

Dimitrakopoulos

Manou

Segev

12:30-14:00 Lunch

14:00-15:00

Plenary


Sergey Foss: Heavy tails in queues



15:05-16:05

M3


Analysis of correlated process

Zverkina

Jacobovic

Batch service system 2

Joshua

De Vuyst

Polling models

Timmerman

Van Ommeren

16:05-16:35 Coffee and Refreshment



16:35-17:15

Ceremony


Takács Dissertation Award: Binyamin Oz



17:30-Tour and dinner: City of David


Tuesday, July 3rd

9:00-10:30

T1


Inventory models

Shajin

Barron

Jacob

Queues with batch arrival

Simonian

Phung-Duc

Boon

Strategic behavior and control 2

Economou

Snitkovsky

Haviv

Coffee and Refreshment


11:00-12:30

T2


Control of fluid systems 2:

Weiss

Qin

Zychlinski

Tandem networks

Lal

Boxma

Baron

Steady state analysis

Raaijmakers

Fralix

Kleiner

12:30-14:00 Lunch

14:00-15:00

Plenary


Bert Zwart: How to handle congestion under uncertainty in power systems using Little

15:10-16:10

T3


Specialized servers

Adan

Fourneau

Dynamics on networks

Patil

Gilboa-Freedman

MAP queueing systems

Punalal

Joshua

16:10-17:00


Coffee and Refreshment

17:00- Tour and Gala dinner: Israel Museum



Wednesday, July 4th

9:30-11:00

W1

Approximations and bounds

Aveklouris

Kalinina

Telek

Retrial queues

Krishnamoorthy

Rumyantsev

Resing

G/G/? systems approximations

Baumann

Bazhba

Sagron

11:00-11:30 Coffee and Refreshment

11:30-12:30

W2

Hitting times

Ravid

Bekker

Fricker

Recourse allocation

Levy

Van Hautegem

Sherzer

Strategic behavior and control 3

Xia

Rangaswamy

Kerner

12:30-14:00 Lunch

14:00-15:00

Plenary


Eli David: Artificial Intelligence

15:10-16:10

W3

System with varying parameters

Viswanath

Ko

Shortest queue analysis

Saxena

Tibi

Farewell, Coffee and Refreshment

Abstracts

Keynotes

Sergey Foss: Heavy tails in queues

I will start with a short overview on 5 possible scenarios that lead to large values of the stationary waiting time in the stable GI/GI/1 queue. Then I plan to talk about various queueing models with heavy-tailed distributions of service times (including multi-server and tandem queues) where a rare event (a large value of a certain characteristic) occurs mostly due to either a single large service time or several large service times, with a further possible influence of normal deviations. In particular, I plan to mention recent works by Blanchet, Rhee and Zwart (with co-authors) and by Miyazawa and Foss. I also plan to consider models with mutually dependent service times and make links to the risk theory.

Bert Zwart: How to handle congestion under uncertainty in power systems using Little

Power systems need to undergo a major transformation in order to handle with uncertainties in supply and demand of electricity. In my vision, this transformation provides research opportunities to queueing theorists, much in the same way as computer-communication networks have done so in the past 50 years. I will illustrate this by surveying some recent work on problems in reliability, storage, and scheduling of electric vehicles.

Eli David: The Deep Learning revolution in practice

During the past few years deep learning (deep neural networks) has revolutionized nearly every field in computer science to which it has been applied, often exhibiting over 20% to 30% improvement over traditional methods in areas such as computer vision, speech recognition, and text understanding. This improvement due to deep learning is arguably the greatest leap in performance in the history of AI. Even though deep learning is a subfield of machine learning, there is a substantial difference between how deep learning and traditional machine learning are applied to various problems, in the sense that deep learning is the only family of methods within machine learning that operates directly on raw data without any feature extraction, and it is capable of effectively training on huge datasets containing hundreds of millions of samples. In this talk we will provide an overview of deep learning and cover some of the groundbreaking real-world results it has achieved recently.

Binyamin Oz:(award winner) Strategic behavior in queues

I will present the first and the third chapters of my PhD dissertation supervised by Prof. Moshe Haviv. The first chapter, entitled “Regulation of queues”, deals with the problem of bridging the gap between selfish and socially optimal joining behavior to queues. We develop new and advantageous regulation methods for observable and unobservable queues. In the third chapter, entitled “State-dependent queues” and co-authored with Ivo Adan, we develop a novel method based on rate conservation argument and exemplify its use in the analysis of non-memoryless queues with state dependent arrival and service processes. Such models typically arise when considering strategic joining to observable non-memoryless queues. I will describe the method, named Rate Balance Principle (RBP), and will use it to derive well-known as well as new results for the G/M/1, G/Mn/1, and Mn/Gn/1 models. More examples, including batch arrivals and server vacations, will be presented if time permits.

Contributed (in alphabetical order)