13 Jul 2021
17 Jul 2021
3rd IEEE International Workshop on Smart & Sustainable Mobility & Logistics in Smart Cities
The workshop, hosted by COMPSAC 2021: Intelligent and Resilient Computing for a Collaborative World, is co-organized by CARS@polito, the interdepartmental center of Politecnico di Torino on Automotive and Mobility, and ICELab@polito, he research center on Smart Cities and Smart logistics.
Call for Papers: SSMLS 2021 – 3rd IEEE International Workshop on Smart & Sustainable Mobility & Logistics in Smart Cities (at COMPSAC 2021)
Virtual conference – July 13-17, 2021
* Important Dates *
Workshop papers due: April 21, 2021
Workshop paper notifications: May 15, 2021
Camera-ready and registration for all papers due: May 31, 2021
* Goal of the workshop *
The workshop aims to foster cooperation among practitioners and researchers in order to exchange the latest industrial experience and research ideas on the development of products and services for smart and sustainable mobility and logistics in Smart Cities.
* Workshop theme *
Urban mobility is one of the toughest challenges we all face today, as existing mobility systems are not smart and sustainable enough to cope with the increasing demand. These issues are real for both passenger and freight mobility. In addition, mobility needs are evolving. Changing travel habits, demand for services to increase convenience, speed and predictability, mobility-as-a-service and e-freight are emerging as new mobility paradigms. Planning and decision-making approaches then are evolving toward a more evidence-based approach, as well as evolving customer expectations toward individualization and sustainability will require mobility service innovation and business model transformation.
* Scope of the workshop *
Researchers and practitioners all over the world, from both academia and industry, working in the areas of Smart Cities, City Logistics, Sustainable Transportation, and Sharing Mobility, are invited to discuss the state of the art solutions, novel issues, recent developments, applications, methodologies, and techniques. Topics of interest include, but are not limited to:
• Cooperative intelligent transportation systems
• Road transport automation
• Electric mobility
• Maps and travel planning
• Mobility modelling
• Behaviour change approaches
• Travel demand estimation and modelling
• Evidence-based planning and decision-making
• Big Data and analytics in transport
• New Business models in mobility and logistics
• Blockchain and trusted network for mobility and logistics
Likely participants: ICT and Smart City researchers are called to participate and exchange ideas and techniques.
* Paper submission *
Workshop papers can be up to 6 pages in length, without additional charge. There is also an option to extend the paper by up to 2 extra pages by paying additional charges.
In order to submit the paper, please register your paper at the following url.
and select the track
[Workshop] SSMLS 2021: Smart & Sustainable Mobility & Logistics in Smart Cities
Accepted papers will be submitted for indexing to IEEExplore.
* Formatting *
Workshop papers are limited to 6 pages. Page limits are inclusive of tables, figures, appendices, and references. Workshop papers can add an additional 2 pages with additional page charges ($250USD/page).
All the papers must be formatted following the guidelines and the templates in
All submissions must use US 8.5×11 letter page format.
* Workshop Chairs *
Dr. Valentina Gatteschi, Politecnico di Torino, Turin, Italy
Dr. Mariangela Rosano, Politecnico di Torino, Turin, Italy
Prof. Layth Sliman, EFREI Engineering School, Paris, France
Prof. Khalil Drira, Laboratoire d’analyse et d’architecture des systèmes, Toulouse, France
Prof. Guido Perboli, Director of the ICT for City Logistics and Enterprises Lab – Politecnico di Torino, Turin, Italy and CIRRELT, Montreal, Canada
07 Jul 2021
09 Jul 2021
Joint EUROPEAN CONFERENCE ON STOCHASTIC OPTIMIZATION and COMPUTATIONAL MANAGEMENT SCIENCE Conference
Joint EUROPEAN CONFERENCE ON STOCHASTIC OPTIMIZATION and COMPUTATIONAL MANAGEMENT SCIENCE Conference
7-9 July 2021, Venice, Italy
The organizers are delighted to invite you to ECSO – CMS 2021 that will be held in Venice, Italy, 7-9 July 2021, at the Department of Economics - Ca’ Foscari University of Venice, in the San Giobbe Economics Campus.
The event was originally planned for July 2020 but due to the COVID-19 situation the conference is rescheduled to the next year.
ECSO - CMS 2021 is jointly organized by the Department of Economics of Ca’ Foscari University of Venice, the CMS Journal and the EURO Working Group on Stochastic Optimization.
ECSO 2021 is the 3rd edition of a stream of conferences organized by the EURO Working Group on Stochastic Optimization (EWGSO). The previous editions were held in Paris (2014) and Rome (2017). The scope of the conference is to bring together researchers and professionals in Stochastic Optimization and its applications in different fields spacing from economics and finance to supply chain, logistics, etc.
CMS 2021 is the 17th edition of an annual meeting associated with the journal of Computational Management Science published by Springer. The aim of the conference is to provide a forum for theoreticians and practitioners from academia and industry to exchange knowledge, ideas and results in a broad range of topics relevant to the theory and practice of computational methods in management science.
This joint event will provide a forum for fruitful discussions and interactions among researchers and professionals from industry and institutional sectors on decision making under uncertainty in a complex world. The conference will be within the scopes of both CMS and EWGSO and, in particular, it will focus on models, methods and computational tools in stochastic, robust and distributionally robust optimization and on computational aspects of management science with emphasis on risk management, valuation problems, measurement applications. Traditional fields of application, such as finance, energy, water management, logistics, supply chain management, and emerging ones, such as healthcare, climate risk and sustainable development, will be included.
CONFIRMED PLENARY SPEAKERS
DARINKA DENTCHEVA, Stevens Institute of Technology (USA)
DAVID MORTON, Northwestern University (USA)
GAH-YI BAN, London Business School (UK)
DANIEL KUHN, École polytechnique fédérale de Lausanne (CH)
GIORGIO CONSIGLI, Università di Bergamo (I)
WARREN POWELL, Princeton University (USA)
Venue: Department of Economics, Ca’ Foscari University of Venice
San Giobbe Campus – Cannaregio 873, 30121 Venice, Italy
Conference Secretariat: firstname.lastname@example.org
Conference hashtag: #ecsocms2021
Call for papers and deadlines will be announced in Autumn
A Best Student Paper Prize will be awarded. Papers should be nominated via e-mail by the students’ supervisors (email@example.com). The program will include a devoted session for presenting the best papers to compete for the prize, such that the jury could make the final choice. The paper does not have to be published. The papers should be principally authored by the student, but co-authors are permitted as long as their contributions are clarified. Only registered participants’ papers will be considered for the prize.
Jury for the Student Best Paper Prize: Stein-Erik Fleten (NTNU Norwegian University of Science and Technology), Milos Kopa (Charles University of Prague), Francesca Maggioni (University of Bergamo), Ruediger Schultz (University Duisburg-Essen).
We are looking forward to seeing you in Venice.
Diana Barro, Stein-Erik Fleten and Martina Nardon
Organizing and Program Committee Chairs
|Department of Economics, Ca’ Foscari University of Venice
07 Jun 2021
11 Jun 2021
Applications of Metaheuristics to large-scale problems
On behalf of the Organizing Committee, we invite you to participate in the
special session (workshop) on
"APPLICATIONS OF METAHEURISTICS TO LARGE-SCALE PROBLEMS" at the 13th
International Conference on
Large Scale Scientific Computation - LSSC'21, June 07 - 11, 2021, Sozopol,
with arrival: June 06 and departure: noon June 11.
The conference web site is regularly updated, see
http://parallel.bas.bg/Conferences/SciCom21/index.html . In particular, we
would like to draw your attention to the information about the Best
Conference Paper Awards.
In accordance with the Announcement, in case of continuing travel
restrictions due to the corona virus, we are ready to create a hybrid
offline online organization to participate in the conference. We would
very much like to hope that this will not be the case.
The session is organized by:
Prof. Stefka Fidanova (firstname.lastname@example.org)
from the Institute of Information and Communication Technologies (former
Institute for Parallel Processing),
Bulgarian Academy of Sciences and
Gabriel Luque (email@example.com) from University of Malaga, Spain.
The list of topics includes, but is not limited to:
optimization in dynamic and/or noisy environments
large scale optimization
parallel and distributed approaches in optimization
random search algorithms,
other derivative free optimization methods
nature inspired optimization methods (evolutionary algorithms,
ant colony optimization, particle swarm optimization, immune artificial
hybrid optimization algorithms involving natural computing techniques
other global and local optimization methods
optimization methods for learning processes and data mining
computational optimization methods in statistics, econometrics, finance,
physics, medicine, biology, engineering etc
We plan to continue publishing the proceedings of only refereed and
presented papers as a
special volume of Springer Lecture Notes in Computer Science (LNCS).
Deadline for submission of abstracts
January 15, 2021
Notification of acceptance of the talks on the basis of the submitted
January 31, 2021
Deadline for registration
February 15, 2021
Deadline for submission of full papers
March 01, 2021
Notification of acceptance of full papers
April 15, 2021
Abstracts and contributed papers
The abstracts (up to 1 page stating clearly the originality of the results)
are to be written in standard LaTeX.
The length of the contributed papers is limited up to 8 pages. It is
assumed that one participant
will present not more than one talk.
Send the abstracts and papers to special session organizers and conference
indicating the name of the special session.
After sending the abstract go to the conference web page and fill in the
registration form (personal data of the participants,
minimum one per paper, and the name of the special session).
Information about abstract and paper preparation, accommodation,
registration form and conference location you can find at the conference
web page http://parallel.bas.bg/Conferences/SciCom21/
Special session organizers
Prof. Stefka Fidanova
Prof. Gabriel Luque
24 Feb 2021
24 Feb 2021
Decision, Decision, Decision!
The University of Portsmouth is delighted to announce the second edition of
the event 'Decision, decision, decision!' a virtual workshop to create
awareness of the usefulness of multicriteria decision making techniques.
The event is organised in collaboration with the INFORMS Section
on Multiple Criteria Decision Making, the EURO Working Group on
Multicriteria Decision Aiding (EWG-MCDA) and the Decision Analysis SIG of
the Operational Research Society.
The workshop will take place online on the 24th of February at 13:00 GMT /
14:00 CET. You can access the event clicking at this link
platform, Passcode 895589).
The plenary speaker of the event is Professor Roman Slowiński, Editor in
Chief of the European Journal of Operational Research.
A detailed program of the event can be found in the attached leaflet and
you can register for free via the Eventbrite platform
We look forward to virtually meeting you on the 24th of February.
Dr Maria Barbati
Senior Lecturer in Business Analytics and Quantitative Research Methods
University of Portsmouth
PBS, Operations & Systems Management Group
Portsmouth PO1 3DE
Prof. Roberto Aringhieri, Ph.D. - Associate Professor
Dipartimento di Informatica, Università degli Studi di Torino
Corso Svizzera 185, I-10149 Torino, Italy
Office: +39 011 6706755 - Mobile: +39 331 1239026
Associate Editor for Operations Research for Health Care
24 Feb 2021
24 Feb 2021
A beautiful paper
Quattro relatori scelgono e "raccontano" quattro articoli, di altri
autori, particolarmente significativi nel campo dell'Ottimizzazione e
della Ricerca Operativa.
Edoardo Amaldi, Renato De Leone, Andrea Lodi, Maria Grazia Speranza
11 Jan 2021
31 May 2021
Upcoming Seminar Series: Machine Learning NeEDS Mathematical Optimization
We warmly welcome you to the Online Seminar Series “Machine Learning NeEDS Mathematical Optimization” that will start on January 11, 2021. This is a weekly seminar series that will take place every Monday, at 16.30 (CET). It will be 100% online-access, and it will have speakers from around the globe.
We have lined up a number of presentations from leading academics in the field of Data Science and Analytics that will cover important topics such as explainability, fairness, fraud, privacy, etc. Mathematical Modeling and Mathematical Optimization will be at the core of their presentations. We will also have presentations from junior academics showing their latest results in this burgeoning area.
For information on the talks follow the link below
Alternatively, you can follow us on Twitter
Looking forward to e-seeing you at the seminar series,
IMUS-Instituto de Matemáticas de la Universidad de Sevilla
Dolores Romero Morales
Copenhagen Business School
IMUS-Instituto de Matemáticas de la Universidad de Sevilla, www.imus.us.es
Copenhagen Business School, www.cbs.dk
H2020 EU RISE NeEDS project, www.riseneeds.eu
||Spain and Denmark
28 Sep 2020
02 Oct 2020
Deep Reinforcement Learning
Organizers: Lihong Li (Google Brain; chair), Marc Bellemare (Google Brain)
The success of deep neural networks in modeling complicated functions has recently been applied by the reinforcement learning community, resulting in algorithms that are able to learn in environments previously thought to be much too large. Successful applications span domains from robotics to health care. However, the success is not well understood from a theoretical perspective. What are the modeling choices necessary for good performance, and how does the flexibility of deep neural nets help learning? This workshop will connect practitioners to theoreticians with the goal of understanding the most impactful modeling decisions and the properties of deep neural networks that make them so successful. Specifically, we will study the ability of deep neural nets to approximate in the context of reinforcement learning.
All events take place in the Calvin Lab auditorium.
Further details about this workshop will be posted in due course. Enquiries may be sent to the organizers at this address.
21 Sep 2020
24 Sep 2020
17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research
We invite you to attend the 17th International Conference on the
Integration of Constraint Programming, Artificial Intelligence, and
Operations Research (https://cpaior2020.dbai.tuwien.ac.at/ ). The aim of
the conference is to bring together interested researchers from
Constraint Programming (CP), Artificial Intelligence (AI), and
Operations Research (OR) to present new techniques or applications and
to provide an opportunity for researchers in one area to learn about
techniques in the others. A main objective of this conference series is
also to give these researchers the opportunity to show how the
integration of techniques from different fields can lead to interesting
results on large and complex problems.
The online conference will take place from September 21 to 24, 2020.
The registration is free of charge:
The conference program is available here:
The conference program includes four invited talks and a Master Class on
the topic ?Recent Advances in Optimisation Paradigms and Solving
? Margarida Carvalho (University of Montreal, Canada): ?Algorithmic
approaches for integer programming games and a story on policy making?
? Georg Gottlob (University of Oxford, UK, and TU Wien, Austria):
?Hypertree Decompositions: Questions and Answers?
? Sebastian Pokutta (Technische Universit?t Berlin, Zuse Institute
Berlin, Germany): ?Restarting Algorithms: Sometimes there is Free Lunch?
? Peter Stuckey (Monash University, Australia) ?Combinatorial
Optimisation for Multi-Agent Path Finding?
Master Class ("Recent Advances in Optimisation Paradigms and Solving
? Laurent Perron and Fr?d?ric Didier (Google Paris, France) ?Constraint
? Armin Biere (Johannes Kepler University, Linz, Austria):
? G?nther Raidl and Andrea Schaerf (TU Wien, Austria, and University of
Udine, Italy): ?(Meta)Heuristics and Hybridisation?
? In?s Lynce (University of Lisbon, Portugal): ?MaxSAT, Multi-Objective
Optimisation, and Parallelism?
? Timo Berthold (Fair Isaac Germany GmbH, Germany):
? Marie Pelleau (Universit? Nice Sophia-Antipolis, France): ?Numerical
CPAIOR 2020 PC Chairs and the Local Organizing Committee
21 Sep 2020
25 Sep 2020
NATCOR Course on Forecasting & Predictive Analysis
The week long course will focus on the principles of time-series forecasting, and recent developments in predictive analytics. Many examples will be used and there will be opportunities for participants to use models ‘hands-on’ and to experiment with real data. Links between forecasting, predictive analytics and decision making under uncertainty will be emphasised. The relevance of forecasting to non-stationary environments will be discussed, for example in inventory, simulation and optimisation models.
Location and Session Leaders
Sessions will be led by experts from the Lancaster Centre for Forecasting, calling on external experts if necessary. The overall co-ordinator will be Professor John Boylan.
The course will be subdivided into three sections, as follows:
•Time series modelling
This forms a natural sequence, moving from univariate models to classical multivariate models to modern methods which address both univariate and multivariate data.
The session on time series modelling will commence with the simplest methods, with opportunities for participants to experiment with parameter choices and to appreciate the scope for parameter optimisation methods to improve forecast accuracy. Model-based approaches will be covered, as well as criteria for choosing between forecasting models. A more general discussion will be held on error measurement and concerns about the reproducibility of forecasting research.
The session on econometric models will start with an introduction to the concepts involved, but will assume some knowledge of regression modelling. It will cover diagnostic analysis of regression models and model choice. This session will also cover some of the important technicalities of econometric time-series models, such as spurious regression, cointegration and modelling non-stationary data. It will conclude with a broader discussion of asymmetric loss functions and forecaster behaviour.
The final session on predictive analytics will cover some key topics for time series analysis. This will include data mining, with a focus on time series clustering for data exploration, and time series classification. It will also cover artificial intelligence for forecasting, focussing on Artificial Neural Networks and recent developments in ensemble methods for forecasting.
14 Sep 2020
26 Sep 2020
CO@Work is a summer school organized by TU Berlin in cooperation with the Berlin Mathematical School and with support of the Berlin Mathematics Research Center MATH+.
TU Berlin BMS MATH+
FICO Gurobi GAMS
This block course targets master students (in their final year), PhD students, and Post-docs interested in the use of combinatorial optimization and mathematical programming in concrete applications from practice. The course schedule covers two weeks with lectures and exercises from 9 am to 5 pm for Monday to Friday, plus half day programs on Saturdays. We plan to have around 25 distinguished lecturers from all over the world, including developers and managers of seven leading companies in the field of mathematical optimization.
Date: September 14 - 26, 2020
Place: Zuse Institute Berlin (ZIB)
ECTS: 10 credit points
Application is open now and will be closed once we reach the capacity limit of 150 participants.
The language of the course is English. There is no participation fee.
We will be able to supply a limited number of travel support grants to students from emerging countries. If you want to apply for a grant, please send an e-mail with a detailed CV and a recommendation letter by a faculty member to firstname.lastname@example.org.
If you need assistance for obtaining a German visa, please contact email@example.com.
Timo Berthold, FICO Xpress
Ksenia Bestuzheva, ZIB
Bob Bixby, Gurobi Optimization
Ralf Borndörfer, FU Berlin
Christina Burt, Water Corporation
Philipp Christophel, SAS
Bistra Dilkina, University of Southern California
Leon Eifler, ZIB
Ivet Galabova, University of Edinburgh
Leona Gottwald, ZIB
Julian Hall, University of Edinburgh
Thorsten Koch, TU Berlin
Pawel Lichoki, Google
Andrea Lodi, GERAD, Polytechnique Montréal
Marco Lübbecke, RWTH Aachen
Robert Luce, Gurobi Optimization
Stephen Maher, University of Exeter
Christoph Moll, Siemens
Marc Pfetsch, TU Darmstadt
Sebastian Pokutta, ZIB and TU Berlin
Güvenç Şahın, Sabancı University
Sabine Seelenmayer, SAP
Stefan Vigerske, GAMS
Sven Wiese, Mosek
CO@Work2020, will be the sixth incarnation of this workshop series, and the fourth one being held in Berlin.
From September 28 to October 10, 2015 more than 160 students from 29 countries, covering all continents except Antarctica, participated in the course held at Zuse Institute Berlin.
From September 21 to October 9, 2009 many students from all over the world participated in the course held at the Zuse Institute Berlin.
From October 4-15 more than 100 students out of 10 countries participated in the course held at the Zuse Institute Berlin.
From September 3-15 parts of the course where discussed during the Görlitz summer school of the German National Academic Foundation.
Beijing 2006 From September 25 to October 6 more than 40 students from all over China attended the course as part of the Workshop Optimization Methods and Applications at the Morningside Center of Mathematics, Chinese Academy of Sciences.
31 Aug 2020
04 Sep 2020
Theory of Reinforcement Learning Boot Camp
Organizers: Csaba Szepesvári (DeepMind & University of Alberta; chair), Emma Brunskill (Stanford University), Sébastien Bubeck (MSR), Alan Malek (MIT), Sean Meyn (University of Florida), Ambuj Tewari (University of Michigan), Mengdi Wang (Princeton)
The Boot Camp is intended to acquaint program participants with the key themes of the program. It will consist of five days of tutorial presentations from leading experts in the topics of the program.
All events take place in the Calvin Lab auditorium.
Further details about this boot camp will be posted in due course. Enquiries may be sent to the organizers at this address.
31 Aug 2020
05 Sep 2020
Mediterranean Machine Learning Summer School
The Mediterranean Machine Learning (M2L) summer school will be structured around 6 days of keynotes, lectures and practical sessions. The program will include social or cultural activities to foster networking and to promote the hosting city. Participants will be encouraged to (optionally) present their work at evening poster sessions during the school and to interact with the main sponsors at their stands/booths during the coffee breaks throughout the week.
Local and international AI experts will teach lectures and laboratories. State-of-the-art content and code will be accessible to all school participants.
Location and dates:
The next edition of the Mediterranean Machine Learning (M2L) summer school will take place in Milan, Italy, from the 31st of August to the 5th of September 2020. The school will be located in the spaces of Università degli Studi di Milano-Bicocca.
The target audience will consist primarily of Master and Doctoral students, academics, and practitioners from all around the world, with a focus on the Mediterranean area. The school will be advertised with a public call and participants will be selected on the basis of merit and to promote diversity. We aim to have around 100 attendees from higher education, with technical background and some understanding and practical experience of machine learning.
|Università degli Studi di Milano-Bicocca, Milan
24 Aug 2020
28 Aug 2020
Third Prague Summer School on Discrete Mathematics
The third edition of Prague Summer School on Discrete Mathematics will be held on August 24-28, 2020 in the historical building of the Computer Science Department of Charles University in the very heart of Prague. Lecture series will be given by Subhash Khot (New York University) and Shayan Oveis Gharan (University of Washington).
The School is primarily intended for PhD students and early career researchers. There is no registration fee and a number of travel stipends will be available.
Previous Schools were held in Prague in 2016 and 2018.
03 Aug 2020
09 Aug 2020
Indonesia has around 3,276 universities, 6,924,511 students, and 247,269 lecturers, yet this country is unnoticed when talking about research, especially in computer science, more specifically in Machine Learning.
According to NIPS 2017 (The biggest conference in Machine Learning) statistics here, none of the authors from 675 accepted papers were affiliated with Indonesian Institutions. This situation can change, India also had zero participant in 2006 but now regularly shows up in many top ML conferences. Brazil starts to follow.
Skills shortages, small funding, infrastructure, and even confidence could be the factors that affect the Indonesian participation levels in top machine learning conferences. Many ML experts, top universities, top conferences, summer schools, and industries are located far away from Indonesia, making it even harder for Indonesian students and researchers to get good exposures in machine learning. Moreover, currently there is no formal program in machine learning or artificial intelligence offered in Indonesian universities.
Therefore, inline as stated at mlss.cc, our mission is to bring the best ML/AI environments closer to Indonesia, so more people can taste machine learning directly from the experts, and eventually more Indonesian talents will get inspired.
29 Jul 2020
06 Aug 2020
Deep Learning and Reinforcement Learning Summer School 2020
About the 2020 Deep Learning and Reinforcement Learning School
In 2005, CIFAR’s Learning in Machines & Brains program hosted its first Deep Learning and Reinforcement Learning Summer School in Toronto with the goal of fostering the next generation of AI researchers. Many of the former students are now leaders at some of the top tech firms and university labs.
Today, the DLRL Summer School is a part of both the CIFAR Learning in Machines & Brains program and CIFAR Pan-Canadian AI Strategy’s National Program of Activities, and is delivered in partnership with Canada’s three national AI Institutes, Mila, Amii and the Vector Institute.
This year’s DLRL Summer School happens July 29 to August 6, 2020 in Montreal, Quebec, Canada. The event brings together graduate students, post-docs and professionals to cover the foundational research, new developments, and real-world applications of deep learning and reinforcement learning. Participants learn directly from world-renowned researchers and lecturers.
Related extracurricular activities will include an AI Career Fair, industry and partner-sponsored events, as well as tourism events.
27 Jul 2020
31 Jul 2020
4th International Summer School on Deep Learning
DeepLearn 2020 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova and Warsaw.
Deep learning is a branch of artificial intelligence covering a spectrum of current exciting research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience.
Most deep learning subareas will be displayed, and main challenges identified through 2 keynote lectures and 24 four-hour and a half courses, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event.
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
27 Jul 2020
31 Jul 2020
Advanced Methods in Operations Research for Logistics and Transportation
Advanced Methods in Operations Research for Logistics and Transportation
In the context of decision-making processes, we use Operations Research methods to understand, predict and optimize the behavior of real-life systems through mathematical models. Operations Research techniques are designed to tackle problems with practical meaning, which are typically very complex. These models and methods have been applied in numerous contexts such as defining public and private policies, and planning processes for government and industry with an exceptionally broad spectrum.
To promote scientific collaboration in research lines that focus on advanced methods in Operations Research
To present state-of-the-art methodologies and problems within the context of Logistics and Transportation.
27 Jul 2020
31 Jul 2020
Many challenging applications in Science and Industry can be formulated as optimization problems. Due to their complexity and hardness often they cannot be solved in an exact manner within a reasonable time; thus approximate algorithms become the main alternatives to solve them thanks to their ability to efficiently explore large search spaces.
Metaheuristics are successful techniques able to solve such complex and hard optimization problems that arise in human activities, such as economics, industry, or engineering, and constitute a highly diverse family of optimization algorithms, each of which shows individual properties, and different strengths.
The international Metaheuristics Summer School is aimed at qualified and strongly motivated MSc and PhD students; post-docs; young researchers, and both academic and industrial professionals to provide an overview on the several metaheuristics techniques, and an in-depth analysis of the state-of-the-art. The main theme of the 2020 edition is “Learning and Optimization from Big Data”, therefore MESS 2020 wants to focus on (i) Learning for Metaheuristics; (ii) Optimization in Machine Learning; and (iii) how Optimization and Learning affect the Metaheuristics making them relevant in handling Big Data.
The courses will be held by world renowned experts in the field, and will be inspected practical aspects on complex combinatorial optimization problems, as well as examples of their successful real-world applications. The participants will have plenty of opportunities for debate and work with leaders in the field, benefiting from direct interaction and discussions in a stimulating environment. They will also have the possibility to present their recently results and/or their working in progress through oral or poster presentations, and interact with their scientific peers, in a friendly and constructive environment.
All participants to the school will be involved in the “Metaheuristics Competition”, where each of them, individually or divided in working groups, they will must develop a metaheuristic solution on the given problem. The top three of the competition ranking will receive the MESS 2020 prize. Further, the students, whose algorithms will rank in the five top of the competition ranking, will be invited to submit a report/manuscript of their work to be published in the special MESS 2020 Volume of the AIRO Springer Series.
MESS 2020 will involve a total of 36-40 hours of lectures, therefore in according to the academic system, all PhD and master students attending to the summer school will may get 8 ECTS points. Further, during the summer school the students will tackle homework, or project development.
Application Deadline: March 5, 2020
Notification acceptance: March 30, 2020
Early Registration: by May 1, 2020
Late Registration: from May 2, 2020
27 Jul 2020
31 Jul 2020
4th Modelling Symposium: Introducing Deep Neural Networks
We are pleased to announce the 4th Modelling Symposium which provides once more a mix of theoretical contents and application-oriented analyses. The next symposium will cover Deep Neural Networks (DNNs) including basic introductions into DNNs, common building blocks, design patterns and architectures, best practices, optimization, applications etc. To this end, we welcome a new tutor -- Prof. Dr. Sebastian Stober.
Goal: Please note that DNNs are complex and that this course will help you to get started with DNN analyses. The workshop provides a general introduction into DNNs covering a wide range of topics. After the 4 days you should have an overview of different DNNs, their strength and weaknesses and which parameters of the model might be important and which ones you might have to tweak. The course will also help you to make decisions about which information/parameter can be important in steps XY and it also helps you to better understand the DNN literature (e.g. whether author's omitted important information about the presented models).
27 Jul 2020
31 Jul 2020
PhD Summer School - "Digital transformation of mobility systems: Operations Research models and methods"
PhD-SUMMER SCHOOL "DIGITAL TRANSFORMATION OF MOBILITY SYSTEMS: OPERATIONS RESEARCH MODELS AND METHODS"
We invite interested PhD students to apply for the summer school on “Digital Transformation of Mobility Systems – Operations Research Models and Methods”. The summer school will take place from July 27th-31st 2020 at the Heilbronn-campus of the Technical University of Munich.
· Claudia Archetti: MILP Formulations for Mobility Problems
· Maximilian Schiffer: Recent and Future Trends in Mobility and Transportation Systems
· Marlin Ulmer: Sequential Decision Processes for Mobility and Transportation
· Thibaut Vidal: Heuristics for Vehicle Routing Problems: Trends, Challenges and Prospects
The summer school is sponsored by TUM School of Management. Participants have to pay a fee of 150€ to cover expenses related to the social program including the conference dinner.
Deadline for applications is March 31, 2020.
Further information and application: https://www.gs.tum.de/adone/summerschool/
26 Jul 2020
31 Jul 2020
The EURO Working Group on Operational Research Applied to Health Services (ORAHS) was formed in 1975 as part of a program for developing special interest groups within the European branch, EURO, of the International Federation of Operational Research Societies, IFORS. The group currently has 242 members from 30 countries, mainly from Europe but also from overseas (e.g., USA, Canada, and Brazil). The group meets for a week each summer in a different, mainly European, host country. Meetings are open to anyone with a quantitative background and/or an interest in the subject area. However, the number of participants can be limited to ensure that an open debate is possible. The objectives of the group are to impart ideas, knowledge and experience on the application of OR approaches and methods to problems in the health services area, mutual support of members, co-operation on joint projects and stimulation of approaches and attitudes in the field of applied Operational Research (http://orahs.di.unito.it/about.html).
University of Vienna, Austria
Faculty of Business, Economics, Statistics Oskar-Morgenstern-Platz 1, A-1090 Vienna
Conference: July 26th –31st, 2020
Abstract submission deadline: February 21st, 2020
Notification of acceptance: March 31st, 2020
Deadline for early registration: April 30th, 2020
Deadline late of registration: May 20th, 2020
The academic sessions, which consist of a combination of plenaries and parallel streams with oral presentations, will take place from Sunday, 26th, to Friday, 31st July 2020. There is also a poster session for students with the best poster being awarded a prize. In addition, we have two outstanding keynote speakers: Prof. Dr. Peter Zweifel, Professor emeritus of the Department of Economics of the University of Zurich, and Prof. Greg Zaric PhD, Faculty Director of Management Science, Ivey Business School, Canada (plus Canada Research Chair in Health Care Management Science). There is also a round table entitled "Challenges and Development in Health Care Prevention” with distinguished national and international researchers and policy makers, moderated by Prof. Dr. Robert Fitzgerald, Head of the Karl Landsteiner Institute for Anaesthsiology and Intensive Care Medicine and Head of the Health Political Forum (https://www.gesundheitspolitischesforum.at/). The social program offers an attractive introduction to Austrian culture and the Austrian heritage (city tour, Schönbrunn Palace tour, Danube boat trip).
Local Organizing Committee
Marion Rauner, University of Vienna, Austria
Patrick Hirsch, University of Natural Resources and Life Sciences, Vienna, Austria
Margit Sommersguter-Reichmann, University of Graz, Austria
Sabine Grahsner, University of Vienna (Secretary)
Lorena Reyes-Rubiano, University of Natural Resources and Life Sciences (Web-Master)
Heads of Austrian OR Society Working Groups (ÖGOR) (e.g., Walter Gutjahr, Tina Wakolbinger)
International Scientific Board Members
Ines Marques (Joint Coordinator), Portugal
Sally Brailsford, Great Britain
Mike Carter, Canada
Maria Captivo (2014), Portugal
Fermín Mallor Giménez (2016), Spain
Joe Viana and Fredrik Dahl (2018), Norway Information/Registration: https://orahs2020.univie.ac.at/
Roberto Aringhieri (Joint Coordinator), Italy
Leonid Churilov, Australia
Evrim Didem Gunes and Tugba Cayirli (2013), Turkey Patrick Soriano (2015), Canada
Christos Vasilakis (2017), Great Britain
|University of Vienna
20 Jul 2020
31 Jul 2020
2020 Gene Golub SIAM Summer School
Theory and Practice of Deep Learning
The eleventh Gene Golub SIAM Summer School will take place from 20 - 31 July 2020 at the African Institute for Mathematical Sciences (AIMS) South Africa in Muizenberg, a small seaside suburb of Cape Town, South Africa
The focus of the school will be the theory, implementation, and application of deep learning based on neural nets with many layers. Students will learn the mathematical underpinnings of deep learning using a combination of functional analysis and optimization theory. They will be introduced to applications that include computer vision, nonlinear programming, and forecasting, in addition to attending lectures by practitioners of deep learning in industry.
The summer school will include an important computing component, in which students will implement deep learning algorithms primarily using Python with TensorFlow and Keras. High performance computing resources will be provided by the AIMS supercomputing facility.
Application deadline :
1 February 2020
Applicants selection :
by 15 March 2020
SIAM Web Site
Contact us : firstname.lastname@example.org
The summer school is being organised by:
AIMS South Africa
University of Oxford
University of Maryland, College Park
The intended audience is graduate students, meaning anyone studying beyond a three- or four-year undergraduate degree. Applicants are expected to have done a significant amount of mathematics and some computing in their studies in order to have the required mathematical and computational background for the summer school. Ideal candidates will be working on a research project that requires the use of deep learning methods.
Applicants selected to participate will pay no registration fee, will be provided with standard student accommodation and meals and their travel expenses will be fully covered.
19 Jul 2020
23 Jul 2020
Euro PhD Summer School in Sustainable Supply Chains
Welcome to Lisbon, to Técnico and to the 2020 Euro PhD Summer School in Sustainable Supply Chains. For one week, PhD students and young researchers have the opportunity to learn more on how operational research methods can support organizations on the design, planning and operation of supply chains towards sustainability goals.
10 Jul 2020
19 Jul 2020
EURO PhD School on Data Driven Decision Making
This EURO PhD School (EPS) will focus on giving participants advanced training on Data Driven Decision Making. There will be a methodological as well as an applied component to this EPS. Methodological training on the role of Mathematical Optimization in Data Science will be given in the format of lectures and computer workshops. The lectures will highlight the mathematical and statistical modeling and numerical optimization behind data analysis and data visualization tools. The computer workshops will make this knowledge actionable. Applications of the acquired knowledge to the modeling of specific industrial problems will be presented by professionals from industry and worked out by the PhD students. Mathematical and statistical models and numerical solution approaches will be developed and communicated, following a collaborative approach, in which the PhD students will work in small groups under the guidance of the instructors.
Institute of Mathematics of the University of Seville
Friday to next Sunday
10-19 July 2020
|Institute of Mathematics of the University of Seville
06 Jul 2020
17 Jul 2020
EURO PhD summer schools on Multiple Criteria Decision Aiding/Making (MCDA/MCDM)
PhD summer schools on Multiple Criteria Decision Aiding/Making (MCDA/MCDM) have been jointly organized by the International Society on Multiple Criteria Decision (MCDM) making and EURO Working Group on Multicriteria Decision Aiding (EWG-MCDA) regularly since 1983. The summer school brings together around 50 PhD students from all over the world and leading scholars of MCDA/MCDM at a venue where all participants live, work, and socialize together for a two-week period. This event has been very successful in educating future generations of MCDA/MCDM scholars and facilitating networking among participants.