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Abstract and Learning Objectives
Business research increasingly considers wicked problems and complex dynamic systems. Analytical models of such problems and systems quickly become untraceable and unsolvable. Given increasing computational power, simulation models provide an alternative tool. They can fuel studies tracing the long-term evolution of systems and comparing the outcomes of alternative scenarios. However, successfully applying simulation modelling for business research requires expertise on applicable simulation paradigms, approaches to model validation and the analysis of stochastic results.

Date of Event:
7. bis 10. Oktober 2019

Location:
Christian-Albrechts-Universität zu Kiel
Wilhelm-Seelig-Platz 1
Raum 505
24118 Kiel


Lecturer:

Prof. Dr. Catherine Cleophas
CAU Kiel

Registration:
To get an overview of the amount of the participation fee and to register for the course, please use this link: http://vhbonline.org/veranstaltungen/prodok/anmeldung/
You can also send an email to prodok(at)vhbonline(dot)org.

Registration deadline: 08. September 2019

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Overview

The Autumn school on Machine Learning will be held in Tbilisi, Georgia, October 3-11, 2019. The school will be organized by the International Black Sea University with the support of Shota Rustaveli National Science Foundation of Georgia (SRNSFG). The intended audience of the autumn school includes BSc, MSc and PhD students, researchers as well as industry professionals.

Organizing Committee

Anna Chutkerashvili, Georgian Technical University / Tbilisi State University
Besik Dundua, International Black Sea University / Tbilisi State University
Cihan Mert, International Black Sea University (chair)
Mikheil Rukhaia, International Black Sea University / Tbilisi State University

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Fall School
This is the webpage of the fall school of the thematic Einstein semester Algebraic Geometry, which is devoted to the study of algebraic geometry and of its applications and is organised by Peter Bürgisser (TU Berlin), Gavril Farkas (HU Berlin) and Christian Haase (FU Berlin).

Times and Venue
The school will take place from the 30th of September 2019 to the 4th of October 2019 at Arnimallee 3 (Room SR 019 and SR 024) in the campus of the Freie Universität Berlin.

Minicourses
Greg Blekherman (Georgia Tech) - Convex and Algebraic Geometry of Sums of Squares on Varieties
A polynomial with real coefficients is called nonnegative if it takes only nonnegative values. For example, any sum of squares of polynomials is obviously nonnegative. The study of the relationship between nonnegative polynomials and sums of squares is a classical area in real algebraic geometry. The minicourse will be about the convex cones of nonnegative polynomials and sums of squares on a variety. Convex-geometric considerations, such as duality and facial structure of these cones will lead to new insights in algebraic geometry. The main questions we will consider are: when are all nonnegative polynomials sums of squares, and the number of squares needed to write a sum of squares.
Dawei Chen (Boston College) - Moduli of differentials and Teichmüller dynamics
An abelian differential defines a flat metric with conical singularities such that the underlying Riemann surface can be realized as a polygon with edges pairwise identified via translation. Varying the shape of such polygons induces a GL(2,R)-action on the moduli space of abelian differentials, called Teichmüller dynamics, whose study has provided fascinating results in many fields. I will give an introduction to this beautiful subject, with a focus on a combination of algebraic, analytic, combinatorial and dynamical viewpoints as well as some recent developments.
Giorgio Ottaviani (University of Florence) - Tensor Rank and Complexity
The asymptotic complexity of the matrix multiplication algorithm is one of the basic open problems in Complexity Theory. In other words, how many operations are needed to multiply two nxn matrices when n is large? The seminal work by Strassen and Bini translated this problem into the computation of the rank and the border rank of certain tensors, which can be studied with tools from Algebraic Geometry, especially in the symmetric case. The symmetric rank of a monomial can be computed by algebraic tools, and already this elementary case is not trivial. In the lectures we will review some important constructions and results in this area, and we will introduce the asymptotic rank, which in turn has a distinguished role in quantum computation. We will expose the recent computation of the symmetric border rank of a monomial by Christandl, Gesmundo and Oneto, by a clever use of the asymptotic rank.
Bernd Sturmfels (MPI Leipzig/Berkeley) - D-Modules and Holonomic Functions
In algebraic geometry we study the solutions of polynomial equations. This is equivalent to studying solutions of linear partial differential equations with constant coefficients. In these lectures we explore the more general case of partial differential equations whose coeffients are polynomials. The letter D stands for the Weyl algebra, and a D-module is simply a left module over D. We focus on left ideals, or D-ideals. These are the systems of linear PDE whose solutions we care about.
Functions in several variables can be modeled by the PDE they satisfy. A comprehensive class of functions with excellent algebraic properties are the holonomic functions. They are encoded by holonomic D-modules. These are useful for many applications, e.g. in geometry, physics and statistics. Course participants will learn how to work with holonomic functions.

Application
Participants must apply at this link. We are working to acquire funding to offer support for travel or accommodation to some participants. The registration will close on the 1st of September 2019.
Due to space limitations and the overwhelming interest in our Fall School we might not be able to accommodate everybody who registered; we reserve the right to reject applications. We will send out notifications in early September.

For any question about this event, you may contact the email address agfallschool2019@gmail.com or one of the organisers of the fall school: Daniele Agostini (HU Berlin), Thomas Krämer (HU Berlin), Marta Panizzut (TU Berlin), Rainer Sinn (FU Berlin).

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EURO is pleased to announce the availability of a limited number of bursaries for PhD students to attend NATCOR (National Taught Course Centre in Operational Research) courses in the UK to PhD students on a number of different topics in OR.

The NATCOR course fees and accommodation (typically bed and breakfast) will be funded by EURO for successful candidates.

Applicants must be PhD students, from one of the EURO member countries or studying in one of the EURO member countries. (see https://www.euro-online.org/web/pages/1457/current-member-societies). Applicants must have good English Language skills as all NATCOR courses will be in English. Preference will be given to students in their first or second years but all are welcome to apply. Preference will also be given to applicants who have not previously received support from EURO for NATCOR or other PhD schools.

To apply for a bursary, candidates from a EURO member society country, or studying in a EURO member society country, should submit a zip file containing the application form, their curriculum vitae (including their academic track record), a letter outlining their motivation to attend, and a letter of recommendation from their supervisor to https://www.euro-online.org/awards/natcor2019/registration.php. Applicants should declare on their application if they are receiving any additional support from their PhD funding body or other sponsor.

Important Dates
Deadline for applications: January 15, 2019
Notification of acceptance: February 4, 2019

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We invite original contributions related to both theoretical and practical aspects of optimization methods. The list of topics includes, but is not limited to:

* combinatorial and continuous global optimization
* unconstrained and constrained optimization
* multiobjective and robust optimization
* optimization in dynamic and/or noisy environments
* optimization on graphs
* large-scale optimization, in parallel and distributed computational environments
* meta-heuristics for optimization, nature-inspired approaches and any other derivative-free methods
* exact/heuristic hybrid methods, involving natural computing techniques and other global and local optimization methods
* numerical and heuristic methods for modeling

The applications of interest are included in the list below, but are not limited to:

* classical operational research problems (knapsack, traveling salesman, etc)
* computational biology and distance geometry
* data mining and knowledge discovery
* human motion simulations; crowd simulations
* industrial applications
* optimization in statistics, econometrics, finance, physics, chemistry, biology, medicine, and engineering.
* environment modeling and optimization

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The best WCO19 paper will be awarded during the social dinner of FedCSIS2019.
The best paper will be selected by WCO19 co-Chairs by taking into consideration the scores suggested by the reviewers, as well as the quality of the given oral presentation.

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Submission and Publication

* Authors should submit draft papers in PDF format.
* The total length of a paper should not exceed 10 pages for regular paper and 4 pages for short papers (IEEE style). IEEE style templates are available at http://www.fedcsis.org/.
* Papers will be refereed and accepted on the basis of their scientific merit and relevance to the workshop.
* Accepted and presented papers will be published in the Conference Proceedings and included in the IEEE Xplore database and submitted for different indexations (Communication and Position papers will only appear in the conference proceedings).
* Extended versions of selected papers presented at WCO19 will be published in edited books of the series "Studies of Computational Intelligence", Springer.

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Important dates:

Paper submission (sharp / no extensions) : May 14th, 2019
Position paper submission : June 4th, 2019
Author notification : June 25th, 2019
Final paper submission and registration : July 10, 2019
Conference date : September 1-4, 2019

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Organizing Committee

Stefka Fidanova, Bulgarian Academy of Science, Bulgaria
Antonio Mucherino, IRISA, University of Rennes 1, France
Daniela Zaharie, West University of Timisoara, Romania

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Call for Papers - Data Science Meets Optimisation (DSO) Workshop at IJCAI-19 (the 28th International Joint Conference on Artificial Intelligence)
August 10-16, 2019, Macao, China

Extended submission deadline: May 27, 2019
(New!!!!) Special issue in the Annals of Mathematics and Artificial Intelligence
Keynote speaker: Prof. dr. Holger Hoos (Leiden University, NL)

*Important dates*

Submission deadline (extended): May 27, 2019
Notification of acceptance: June 15, 2019

*Scope*

Data science and optimisation are closely related. On the one hand, many problems in data science can be solved using optimisers, on the other hand optimisation problems stated through classical models such as those from mathematical programming cannot be considered independent of historical data. Examples are ample. Machine learning often relies on optimisation techniques such as linear or integer programming. Algorithms may be complete, approximative or heuristic and may be applied in on-line or off line settings. Reasoning systems have been applied to constrained pattern and sequence mining tasks. A parallel development of metaheuristic approaches has taken place in the domains of data mining and machine learning. In the last decades, methods aimed at high level combinatorial optimisation have been shown to strongly profit from configuration and tuning tools building on historical data. Algorithm selection has since the seventies of the previous century been considered as a tool to select the most appropriate algorithm for a given instance. Empirical model learning uses machine learning models to approximate the behaviour of a system, and such empirical models can be embedded into an optimisation model for efficiently finding an optimal system configuration.

The aim of the workshop is to organize an open discussion and exchange of ideas by researchers from Data Science and Operations Research domains in order to identify how techniques from these two fields can benefit each other. The program committee invites submissions that include but are not limited to the following topics:
- Applying data science and machine learning methods to solve combinatorial optimisation problems, such as algorithm selection based on historical data, speeding up (or driving) the search process using machine learning, and handling uncertainties of prediction models for decision-making.
- Using optimisation algorithms in developing machine learning models: formulating the problem of learning predictive models as MIP, constraint programming (CP), or satisfiability (SAT). Tuning machine learning models using search algorithms and meta-heuristics. Learning in the presence of constraints.
- Embedding methods: combining machine learning with combinatorial optimization, model transformations and solver selection, reasoning over Machine Learning models.
- Formal analysis of Machine Learning models via optimization or constraint satisfaction techniques: safety checking and verification via SMT or MIP, generation of adversarial examples via similar combinatorial techniques.
- Computing explanations for ML model via techniques developed for optimization or constraint reasoning systems
- Applications of integration of techniques of data science and optimization.

*Submission*

We invite the following submissions (all in the IJCAI proceedings format, see: https://www.ijcai.org/authors_kit ):
- Submission of original work up to 8 pages in length.
- Submission of work in progress (with preliminary results) and position papers, up to 6 pages in length.
- Published journal/conference papers in the form of a 2-pages abstract.
The program committee will select the papers to be presented at the workshop according to their suitability to the aims.
Contributors of the workshop will be invited to submit full versions of their papers for inclusion in a special volume of the Annals of Mathematics and Artificial Intelligence, published by Springer.
Those invited submissions will be subject to refereeing at the usual standards of the journal, and authors will receive more details with the acceptance notice.

Submissions through: https://easychair.org/conferences/?conf=ijcai2019dso


*Workshop organizers*

Patrick De Causmaecker (KU Leuven, BE), patrick.decausmaecker@kuleuven.be
Michele Lombardi (University of Bologna, IT), michele.lombardi2@unibo.it
Yingqian Zhang (TU Eindhoven, NL), yqzhang@tue.nl

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The 2nd Advanced Course on Data Science & Machine Learning (ACDL) is a full-immersion five-day residential Course at the Certosa di Pontignano (Siena – Tuscany, Italy) on cutting-edge advances in Data Science and Machine Learning with lectures delivered by world-renowned experts. The Course provides a stimulating environment for academics, early career researches, Post-Docs, PhD students and industry leaders. Participants will also have the chance to present their results with oral talks or posters, and to interact with their peers, in a friendly and constructive environment.
You will gain a heightened awareness for fields of data science and machine learning relevant for your activity and, perhaps most important, you will gain a place within an elite global network of data scientists and machine learning experts.
The Advanced Course is not a summer school suited only for younger scholars. Rather, a significant proportion of seasoned investigators are regularly present among the attendees, often senior faculty at their own institutions. The balanced audience that we strive to maintain in each Advanced Course greatly contributes to the development of intense cross-disciplinary debates among faculty and participants that typically address the most advanced and emerging areas of each topic.
Each faculty member presents lectures and discusses with the participants for one entire day. Such long interaction together with the small, exclusive Course size provides the uncommon opportunity to fully explore the expertise of each faculty, often through one-to-one mentoring. This is unparalleled and priceless.
The Course will involve a total of 36-40 hours of lectures, according to the academic system the final achievement will be equivalent to 8 ECTS points for the PhD Students and the Master Students attending the summer school.
The Certosa di Pontignano provides the perfect setting to a relaxed yet intense learning atmosphere, with the stunning backdrop of the Tuscan landscapes. World-class wines and traditional foods will make the Advanced Course on Data Science & Machine Learning the experience of a lifetime.

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The ECMI Postgraduate / VI Iberian / NeEDS Modelling Week will be held at the Mathematical Institute of the University of Seville https://www.imus.us.es/en/ (Seville, Spain) on July 7th-13th, 2019. It is co-organized by the European Consortium for Mathematics and Industry (https://ecmiindmath.org/), the Spanish Network for Mathematics-Industry (http://www.math-in.net/?q=en), the Portuguese Network of Mathematics for Industry and Innovation (https://www.spm.pt/PT-MATHS-IN/), and the H2020-MSCA-RISE NeEDS project (http://www.riseneeds.eu/), and takes part of the satellite meetings to the 9th International Congress on Industrial and Applied Mathematics https://iciam2019.org/ (July 15th-19th, 2019, Valencia, Spain).

The format of the Modelling Week is to spend one week working to solve real problems that can be tackled through mathematical modeling. Small groups of multinational Master students, Ph.D. students and junior researchers (like post-doctoral students) will be assigned to each problem in term of their preference and own skills on the first day of the event after the presentation of the problems. An instructor, that must be an expert in the area, of the proposed problem leads each of these groups. During the following four days students will work on solving the problems under the guidance of the instructor and industrial collaborators. Last day of the meeting will be devoted to the presentation of the results, which will be collected in the proceedings of the event.

To register for this modeling week, please follow the link
http://gestioneventos.us.es/22663/section/15646/ecmi-postgraduate-vi-iberian-needs-modelling-week.html
For information on competitive financial support, please follow the link
http://gestioneventos.us.es/22663/section/16752/ecmi-postgraduate-vi-iberian-needs-modelling-week.html

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EURO is pleased to announce the availability of a limited number of bursaries for PhD students to attend NATCOR (National Taught Course Centre in Operational Research) courses in the UK to PhD students on a number of different topics in OR.

The NATCOR course fees and accommodation (typically bed and breakfast) will be funded by EURO for successful candidates.

Applicants must be PhD students, from one of the EURO member countries or studying in one of the EURO member countries. (see https://www.euro-online.org/web/pages/1457/current-member-societies). Applicants must have good English Language skills as all NATCOR courses will be in English. Preference will be given to students in their first or second years but all are welcome to apply. Preference will also be given to applicants who have not previously received support from EURO for NATCOR or other PhD schools.

To apply for a bursary, candidates from a EURO member society country, or studying in a EURO member society country, should submit a zip file containing the application form, their curriculum vitae (including their academic track record), a letter outlining their motivation to attend, and a letter of recommendation from their supervisor to https://www.euro-online.org/awards/natcor2019/registration.php. Applicants should declare on their application if they are receiving any additional support from their PhD funding body or other sponsor.

Important Dates
Deadline for applications: January 15, 2019
Notification of acceptance: February 4, 2019

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There will be a workshop in Edinburgh titled "Advances in Linear Algebra and Huge-Scale Optimization" with the following list of invited speakers:

Luca Bergamaschi, Università degli Studi di Padova
Jordi Castro, Universitat Politècnica de Catalunya
Daniela di Serafino, Università degli Studi della Campania
Anders Forsgren, KTH Royal Institute of Technology
Daniel Loghin, University of Birmingham
Benedetta Morini, Università di Firenze
Miroslav Rozložník, Czech Academy of Sciences
Ekkehard Sachs, Universität Trier
David Silvester, University of Manchester
Jemima Tabeart, University of Reading

The registration is free, but if you plan to attend please do register as we need this information for catering purposes.

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CNR-IASI, as part of the Marie Sklodowska-Curie ETN MINOA (http://minoa-itn.fau.de), announces the school for PhD students and post-docs on the theme "Mixed Integer Non linear Optimization meets Data Science".

The school will be held on June 25-28, 2019 in Ischia (Italy) at Hotel Hermitage.

The topics and the lecturers will be the following:

Deep Learning for AI - by Yoshua Bengio (University of Montreal, CANADA)
Clustering for Big Data - by Ravi Kumar (Google, US)
Machine Learning for Combinatorial Optimization - by Andrea Lodi (Polytechnique Montréal, CANADA)
Support Vector Machines - by Laura Palagi (Sapienza Università di Roma, ITALY).

The school will also include two industrial demonstration by:
Pierre Bonami (IBM, FRANCE)
Joaquim Gromicho (ORTEC, THE NETHERLANDS)

For more information and registrations please visit the web page

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The Hunter Centre for Entrepreneurship, Strathclyde Business School, University of Strathclyde in collaboration with the Research Infrastructure for Science and Innovation Policy Studies (RISIS) Project (EU H2020 Grant Agreement n°824091) is delighted to announce the Summer School on Data Science for Studying Science, Technology and Innovation to be held in Glasgow, UK, 24th – 28th June 2019.
Objectives: The RISIS project aims to transform the field of Science and Innovation Policy (STI) studies into an advanced research community. As part of this mission, the Summer School on Data Science for Studying Science, Technology and Innovation will bring together leading experts in data science and the next generation of STI scholars. The aim is to develop both the methodological and conceptual knowledge as well as cutting edge data science tools and techniques. The summer school also acts as a platform to develop of a community of emerging scholars and to facilitate future collaborations. The course is open to all career levels including PhD researchers, early career and established scholars.
Expected Outcomes:
At the end of the course, participants will become familiar with:
- The basic workflow of data science
- Critical choices needed to conduct a data science analysis with publication data as well as the assumptions behind metrics and approaches
- Advanced analysis of publication data through descriptive and exploratory modelling, network analysis and text-mining
- R as the rapidly becoming standard data science tool
Target Audience:
The Summer School targets scholars and policy analysts studying STI at all stages from PhD researchers through to established scholars. The target group will have some experience with the basic quantitative methods in the topic, while the Summer School will help them to reach to a more advanced level of understanding.
Teaching Style:
The summer school is designed as interactive learning. All sessions will include hands-on exercises (at least 1/3 of the time) in which participants would address practical questions in groups and present their findings. All sessions will utilise a sub-sample of the KNOWMAK dataset.

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Machine Learning is a key to develop intelligent systems and analyze data in science and engineering. Machine Learning engines enable intelligent technologies such as Siri, Kinect or Google self driving car, to name a few. At the same time, Machine Learning methods help deciphering the information in our DNA and make sense of the flood of information gathered on the web, forming the basis of a new “Science of Data”. This course provides an introduction to the fundamental methods at the core of modern Machine Learning. It covers theoretical foundations as well as essential algorithms. Classes on theoretical and algorithmic aspects are complemented by practical lab sessions.


This introductory course is suitable for undergraduate/graduate students, as well as professionals.


Course Structure:

06/17 Monday 9:30-13:00 Lessons - 14:00-16:00 Laboratory
06/18 Tuesday 9:30-13:00 Lessons - 14:00-16:00 Laboratory
06/19 Wednsday 9:30-12:30 Talks
06/20 Thursday 9:30-13:00 Lessons - 14:00-16:00 Laboratory
06/21 Friday 9:30-13:00 Lessons

The course started in 2013 has seen an increasing national and international attendance over the years with a peak of over 100 participants in 2015.


Important dates:

application deadline: April 19
notification of acceptance: TBA
registration fee deadline: TBA

Registration fee (note):

students and postdocs: EUR 50
professionals: EUR 150
UNIGE students and IIT affiliates: no fee
Once accepted, each candidate has to follow the instructions in the acceptance email and proceed with the payment.

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Since 1990, DISC has successfully organized yearly summer schools on various topics pertinent to theoretical and practical aspects of systems and control, with an international audience of about 40-60 participants. Together with the graduate course program that is maintained by DISC, the summer schools form part of the educational facilities that DISC offers to PhD students in systems theory and control engineering. The main goal of the summer schools is to familiarize young researchers with recent developments in systems and control as well as in neighboring disciplines, and to provide them with the opportunity to enjoy, in an informal atmosphere, discussions with top researchers in systems and control. The summer schools also provide an opportunity for DISC staff members and others to upgrade their knowledge of specific areas of interest.

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The Swiss Operations Research Days are a unique opportunity for researchers from the Swiss academic community and Operations Research professionals in Swiss enterprises and public organizations to learn about each other’s work and interests and to exchange current research developments in Operations Research. The aim is not just to exchange knowledge, but to promote collaboration, initiate new projects and to have a good time with inspiring discussions. Jointly organized by UNIL and SVOR/ASRO, and sponsored by SVOR/ASRO, the 17th Swiss OR Days will take place at the University of Lausanne on June 6th and June 7th, 2019.

Plenary Speakers:

Prof. Dr. Nils Boysen, Friedrich-Schiller-Universität Jena
Dr. Judit Lienert, Eawag (Swiss Federal Institute of Aquatic Science and Technology), Dübendorf
Dr. Marco Laumanns, Bestmile SA, Lausanne
Please send your abstract for a contributed talk by May 10th, 2019 at the latest.

Please register for the event by May 24th, 2019 at the latest.

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Many real systems can be modeled as networks, where the elements of the system are nodes and interactions between elements are edges. An even larger set of systems can be modeled using dynamical processes on networks, which are in turn affected by the dynamics. Networks thus represent the backbone of many complex systems, and their theoretical and computational analysis makes it possible to gain insights into numerous applications. Networks permeate almost every conceivable discipline —including sociology, transportation, economics and finance, biology, and myriad others — and the study of “network science” has thus become a crucial component of modern scientific education.

The school “Complex Networks: Theory, Methods, and Applications” offers a succinct education in network science. It is open to all aspiring scholars in any area of science or engineering who wish to study networks of any kind (whether theoretical or applied), and it is especially addressed to doctoral students and young postdoctoral scholars. The aim of the school is to deepen into both theoretical developments and applications in targeted fields.

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EURO is pleased to announce the availability of a limited number of bursaries for PhD students to attend NATCOR (National Taught Course Centre in Operational Research) courses in the UK to PhD students on a number of different topics in OR.

The NATCOR course fees and accommodation (typically bed and breakfast) will be funded by EURO for successful candidates.

Applicants must be PhD students, from one of the EURO member countries or studying in one of the EURO member countries. (see https://www.euro-online.org/web/pages/1457/current-member-societies). Applicants must have good English Language skills as all NATCOR courses will be in English. Preference will be given to students in their first or second years but all are welcome to apply. Preference will also be given to applicants who have not previously received support from EURO for NATCOR or other PhD schools.

To apply for a bursary, candidates from a EURO member society country, or studying in a EURO member society country, should submit a zip file containing the application form, their curriculum vitae (including their academic track record), a letter outlining their motivation to attend, and a letter of recommendation from their supervisor to https://www.euro-online.org/awards/natcor2019/registration.php. Applicants should declare on their application if they are receiving any additional support from their PhD funding body or other sponsor.

Important Dates
Deadline for applications: January 15, 2019
Notification of acceptance: February 4, 2019

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The 8th edition of the Winter School on Network Optimization will take place at Hotel Estoril-Éden, Monte Estoril, from the 14th to the 18th of January 2019. Its main objective is to provide an opportunity for PhD students to get together and attend high level courses in the field of Network Optimization. Non-PhD students are welcome to attend the school, but the number of participants is limited and priority will be given to PhD students. In this edition of the school, the lecturers and subjects to be addressed are:

Markus Leitner (Univ. of Vienna) - Layered graph approaches for combinatorial optimization problems;
William Cook (Univ. of Waterloo) - The Traveling Salesman Problem and Computational Discrete Optimization;
Giovanni Rinaldi (IASI) - Maximum weight cuts in graphs and extensions;
Francisco Saldanha da Gama (Univ. de Lisboa) - Logistics network design: capturing uncertainty and risk;
Tolga Bektas (Univ. of Southampton) - Compact formulations, projections and some polyhedral results for the vehicle routing problem.

The school is part of the activities of the of the ENOG (European Network Optimization Group) and of CMAFCIO (Centro de Matemática, Aplicações Fundamentais e Investigação Operacional) University of Lisbon. The event is also endorsed by the EURO (the Association of European Societies) and APDIO (the Portuguese OR society). Potential participants are invited to submit their CVs to the address NetOpt2019@fc.ul.pt no later than the 31st October .

(Further information is available in the link)

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The 3rd Grid Science Winter School and Conference will cover theoretical and algorithmic aspects of electrical and interdependent networks that have immediate and potential future importance to the research community. The areas of focus for this incarnation of the Winter School and Conference are emerging from theoretical needs perceived within DOE Office of Electricity, the Grid Modernization Initiative, and ARPA-E. Several of these needs are challenging crosscuts between related, but often isolated, research areas, including Analysis, Optimization, Control and Machine Learning over Physical Networks.

Consistent with previous editions, the entire event will last for five days (January 7-11, 2019) -- three days of the Winter School followed by two days of the Conference, with the exact proportion to be determined based upon availability of the lecturers and seminar speakers. The Winter School portion will consist of 9 lecture blocks (each block representing a subject) given in three days to roughly 30-40 graduate students and postdocs chosen via an application and screening process to ensure high quality attendees that are able to extract the maximum possible from the event. To ground the students and to establish a common frame of conference for the following theoretical topic areas, the School will open with overview presentations on the the physics and engineering of the energy networks. This introduction will be followed by a series of lectures that introduce the students to a range of advanced theoretical topics that are not typically available at their home institutions. The approximately 90 minute lectures will consist of a general introduction to the area and in depth discussion of examples to provide a more solid understanding of the approaches. The intent is not to make the students immediately able to apply the theoretical techniques, but rather to demonstrate the usefulness of the methods, stimulate interest in them, and develop crosscutting collaboration between students from different disciplines.

The Winter School is followed by the Conference consisting of presentations by established and emerging top researchers in theoretical methods applied to energy networks. Robust discussion and debate of topics will be encouraged. Each junior attendee of the Winter School will be required to present a poster and a committee of judges will select several posters for presentation at the Conference.

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1st International Summer School "SMART CITY looks like"
Building the Cities of the Future

July 16th - 25th, 2018 2018, at Eurasian National University (ENU) - Astana, Kazakhstan

GOAL
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By participating in the International Summer School "SMART CITY LOOKS LIKE" students will explore interdisciplinary approaches while working in interdisciplinary and intercultural groups of students and lecturers in order to analyze what smart city looks like: cities aiming to become more energy efficient, clean and green, while addressing Citizen engagement, governance and critical needs.

TOPICS
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The school is interdisciplinary and will cover topics in both ICT and other relevant areas. In particular, the school will include lectures on wireless sensor network technologies, open data, urban data analytics, cybersecurity, as well as, mobility, sustainability, energy and urban planning.

PREREQUISITE
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Students of all levels are welcome. ICT students, Msc Student, PhD students and researchers at the early stage of their career are particularly encouraged to apply.
English proficiency is required for all summer school programs offered by University of Milano-Bicocca.

REGISTRATION
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Attendance is open to International students. Applications are processed first-come-first-serve, but we reserve the right to exclude applicants whose profile is not well-aligned with the course's prerequisites.
The deadline for the first call of application is March 18th, 2018; notifications of acceptance will be given continuously as the applications come in.

VENUE
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The summer school will take place at the ENU's main campus in Astana, a city with big plans of development situated in a country that has a clear social-oriented program, based on a new quality of life for the greatest possible number of citizens focused on the modernization of the society and the state on the basis of industrial-innovative development.
The exact location on campus and some more practical details will be announced to participants together with the notification.

Participation to the school is 480€ and includes accommodation and lectures as such with accompanying material, exercises, visits and social events connected to the program.

WEB SITE
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The course Web Site is found at http://www.summerschoolbicocca.com/018-07-smart-city-looks-like.php and will be updated continuously.

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The École des Ponts ParisTech will organize a Summer School on the interactions between Operations Research and Machine Learning, which will be held June 25 - 29, 2018 in Fréjus (French Riviera), with the following lecturers:

Sébastien Bubeck (Microsoft Research): Introduction to Statistical Learning Theory
Marco Lübbecke (Aachen University): Title coming soon
Yinyu Ye (Stanford University): Data Driven Optimization and Applications

Note that it takes place precisely the week before ISMP 2018, which will also be held in France.

Location. Villa Clythia in Fréjus, a wonderful resort of the French Riviera.
Registrations. Not open yet
Organizers. Axel Parmentier and Frédéric Meunier
Sponsor. The "Operations Research and Machine Learning" chair of Air France and École des Ponts ParisTech

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The 6th Student Conference on Operational Research will take place at the University of Nottingham from April 6th – 8th 2018.

The Student Conference on Operational Research is a bi-annual meeting where you can showcase your work, establish new connections, and share your experiences. We are pleased to invite PhD students and postgraduate students working in the Operational Research and Managerial Sciences. Our goal is to create a friendly environment where you can talk to colleagues of similar interests, receive constructive feedback and learn about edge cutting applications of Operational Research. The scientific program will include keynote speeches, parallel sessions and workshops. While the scientific program satisfies our intellects the social program will include activities where you can meet and network with fellow students.

In addition to abstract submission, you are invited to submit full papers to be electronically published as part of conference proceedings. Abstracts should contain a maximum of 250 words and 3 to 5 keywords. Full paper submissions must be 10 pages long at most.

The conference precedes the NATCOR course “Heuristics and Approximation Algorithms”, on the Jubilee Campus, University of Nottingham. We look forward to seeing you there.

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We are pleased to announce the 2nd AIROYoung Workshop which will take
place on March 1-2 at the University of Calabria, Italy, on the topic:
Logistics Optimisation and Applied Operational Research.

AIROYoung is the youth chapter of AIRO, the Italian O.R. Society. The
AIROYoung workshop is the perfect venue for PhD students and young
researchers to showcase their work, get feedback and network.

To increase the participation of young researchers, we offer the
following support:
* No enrollment fee;
* Free accommodation for 3 nights (28 Feb, 01 and 02 Mar);
* Free meals (2 lunches and one social dinner);
* Free shuttle from Lamezia Terme Airport (SUF).
Travel support is offered on a first-come, first-serve basis, until
there are available funds.

This year's invited speakers are:
* Geir Hasle, Acting Research Manager, Group of Optimisation,
Mathematics and Cybernetics, SINTEF Digital (Oslo, Norway)
* Roberto Roberti, Assistant Professor in Logistics, School of
Business and Economics, Vrije Universiteit (Amsterdam, the
Netherlands)

Contributed talks are welcome on all topics pertaining to O.R.

Other information can be found at the workshop's website:
https://workshop.airoyoung.org/

The organising committe,
Annarita De Maio
Giusy Macrina
Rosario Paradiso
Vittorio Solina

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2018 School on Column Generation

REGISTRATION IS OPEN, SPACE IS LIMITED.

The 2018 School on Column Generation is the fourth of its kind (after
Paris, France, in 2014, Darmstadt, Germany, in 2010 and Montréal, Canada,
in 2006) and aims at teaching the state-of-the-art in column generation and
branch-and-price to advanced students and PhD students but also to
practitioners and researchers interested. The lectures will be given by
renowned scientists in the field, complemented by hands-on experience in a
computer lab. The participants will have the opportunity to present their
own research or application problems in order to foster discussions and
create a real workshop atmosphere.

Topics to be covered include: Basic theory (decompositions, reformulations,
convexification, discretization, etc.), vehicle routing and crew scheduling
applications, shortest path subproblems, column generation heuristics,
master problem issues (stabilization, aggregation), branching and cutting,
and hints on implementation issues. In particular, on Thursday, we will
spend a whole day with the SCIP framework and learn about implementing
branch-price-and-cut.

Lectures are given by Guy Desaulniers, Jacques Desrosiers, Marco Luebbecke
and Roberto Wolfler-Calvo.

The practical session with SCIP/GCG is given by Jonas Witt.

The program starts on Monday at 9.00 and ends on Friday around 17.00, so we
will have five full days of school.

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Practical application of Operations Research to real-life cases is normally aimed at “optimising” some aspects of the process under study, and measuring and communicating the impacts of the project is key to project’s success (and indeed the whole value proposition). Sharing experiences, best practices and potential risks across a vast panel of OR practitioners presents a great opportunity to ensure adequate visibility to the value OR generates.