ENOG February 2020

enog@mail.euro-online.org

4 participants
5 discussions

Winter School Netopt2020 (1st announcement)
by Luis Eduardo Neves Gouveia 06 Apr '20

06 Apr '20

? The 9th edition of the Winter School on Network Optimization will take place at Hotel Estoril-Éden, Monte Estoril, from the 20th to the 24th of January 2020. 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: Arie Koster (RWTH Aachen University) - Robust Network Optimization; Elena Fernandez (Universidad de Cadiz) - Formulations for Location-Routing; Hande Yaman (KU Leuven) - Hub Location Problems; Ivana Ljubic (ESSEC Business School of Paris) - Branch-and-Benders-cut algorithms: modern implementations of Benders Decomposition; Mario Ruthmair (University of Vienna))- Optimization in Social Networks? The school is part of the activities of the of the ENOG (European Network Optimization Group). 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 netopt2020(a)fc.ul.pt no later than the 31st October. Further information is available in the webpage (http://netopt2020.campus.ciencias.ulisboa.pt<http://netopt2020.campus.ciencias.ulisboa.pt/>) ?

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MESS 2020 ~ Learning & Optimization from Big Data ~ Catania, 27-31 July 2020
by Mario Pavone 20 Feb '20

20 Feb '20

Call for Participation (apologies for multiple copies) ### with kind request to forward it in your contact list (emails, blogs, social networks, etc.)! Thanks ### ----------------------------------------------------------------------- MESS 2020 - Metaheuristics Summer School - Learning & Optimization from Big Data - 27-31 July 2020, Catania, Italy https://www.ANTs-lab.it/mess2020/ mess.school(a)ANTs-lab.it https://www.facebook.com/groups/MetaheuristicsSchool/ ----------------------------------------------------------------------- *** LESS ONCE MONTH LEFT!!! *** ** APPLICATION DEADLINE: 5th March 2020 ** https://www.ants-lab.it/mess2020/application/ MESS 2020 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. All 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. Participants will be delivered a certificate of attendance indicating the number of hours of lectures (36-40 hours of lectures). In according to the academic system all PhD and master students attending to the summer school will may get 8 ECTS points. ** LIST OF LECTURERS + Angelo Cangelosi, University of Manchester & Alan Turing Institute, UK + Swagatam Das, Indian Statistical Institute, Kolkata + Luca Maria Gambardella, IDSIA Istituto Dalle Molle for Artificial Intelligence, Switzerland + Salvatore Greco, University of Catania, Italy & University of Portsmouth, UK + Emma Hart, Edinburgh Napier University, UK + Mauricio Resende, AMAZON, USA + Roman Slowinski, Pozna? University of Technology, Poland + El-Ghazali Talbi, University of Lille 1, France + Daniele Vigo, University of Bologna, Italy More Lecturers will be announced soon. ** SCHOOL DIRECTORS + Pascal Bouvry, University of Luxembourg, Luxembourg + Salvatore Greco, University of Catania, Italy + Ender Ozcan, University of Nottingham, UK + Mario Pavone, University of Catania, Italy + El-Ghazali Talbi, University of Lille 1, France + Daniele Vigo, University of Bologna, Italy ** METAHEURISTICS COMPETITION All participants to the school will be involved in the ?Metaheuristics Competition?, where each of them will must develop a metaheuristic solution on the given problem. The top three of the competition ranking will receive the MESS 2020 prize. Students whose algorithm will rank in the first 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. ** METAHEURISTICS COMPETITION CHAIRS + Raffaele Cerulli, University of Salerno, Italy + Andrea Schaerf, University of Udine, Italy ** SHORT TALK & POSTER PRESENTATION All participants may submit an abstract of their recent results, or works in progress, for presentation and having the opportunities for debate and interact with leaders in the field. Mini-Workshop Organizers and Scientific Committee will review the abstracts and will recommend for the format of the presentation (oral or poster). All abstracts will be published on the electronic hands-out book of the summer school. The Abstracts must be submitted by *March 5, 2020*. ** WORKSHOP CHAIRS + Vincenzo Cutello, University of Catania, Italy + Paola Festa, University of Naples ?Federico II?, Italy + Isaac Triguero, University of Nottingham, UK *See Previous Edition - MESS 2018* https://www.ants-lab.it/mess2018/ ** MORE INFORMATION: https://www.ANTs-lab.it/mess2020/ -- mess.school(a)ANTs-lab.it Facebook Group: https://www.facebook.com/groups/MetaheuristicsSchool/ Twitter: https://twitter.com/MESS_school

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PhD Scholarship.
by Francisco Saldanha da Gama 18 Feb '20

18 Feb '20

Dear Members of ENOG, I would like to draw your attention to the following announcement on a PhD scholarship at The Polytechnic University of Hauts-de-France, Valenciennes, France. I thank you in advance for disseminating this announcement. Best regards, Francisco. ____________________________________________ Multi-period stochastic programming models and techniques for logistics distribution systems. In general problems addressed in the literature are more and more complex and integrate more and more information, thanks to the emergence of new technologies. However, studied problems still represent in most of the cases simplified versions of something that happens in the reality. For example, one aspect that is usually neglected in the literature is the aspect of stochasticity. More precisely, it is assumed that all data are given in advance, and there is nothing that could perturb the data. However, in the reality we have the opposite. There is a lot of uncertainty and systems and their data are subject to perturbations and changes. Hence, the aim of this PhD thesis is to further reduce this existing gap between the literature and practice. This would be achieved by proposing corresponding mathematical models and solution frameworks capable to deal with complex, stochastic problems usually encountered in practice. This thesis will focus on an integrated problem of network design and vehicle routing. The first problem to study will be a hub location routing problem. This problem is faced in many large companies like AMAZON, DHL, FeedEX etc. It consists in satisfying the customer demands within a given planning horizon using a distribution network that needs to be constructed and a given fleet of vehicles. The aim is to determine hub and spoke network through which the demands are transferred and to determine vehicles’ routes. Each demand is processed first at a distribution center, then it is transferred to one or more intermediated hubs, and finally to a customer. The transfers through the network are accomplished by the traditional vehicles (e.g., trucks) except for the last mile delivery where the delivery nowadays is accomplished also by (unmanned aerial vehicles) UAVs and electric vehicles. The second problem is a location arc routing problem. The aim of the problem is to simultaneously determine depots (i.e., locations from where vehicles departs and returns to), and design vehicles’ routes so that prespecified objective function is minimized. In addition, all demands located along edges need to be satisfied. In the frame of this thesis we are going to extend the studied problems by considering important aspects usually encountered in the practice: the aspect of stochasticity/ uncertainty that usually occurs in demands and travel times; and the aspect of multi-periodicity where the decisions need to be provided for a given planning horizon. Hence, the thesis will provide a thorough study on a robust network design and vehicle routing planning, with special emphasize on the stochasticity and multi-periodicity of problems under study. Modeling and studying theoretical properties will be the first step in the solution process of a problem at hand. Due to stochasticity/ uncertainty and/or multi-periodicity of the problems, the obtained models will be large scale mixed integer nonlinear problems. Therefore, the exact methods would be used to solve small test cases, in order to validate approach, while for large scale test cases we will be obliged to resort to heuristic solution approaches. In addition, in order to come up with strong upper/lower bounds, hybridization of exact and heuristic solution approaches will be considered as well. The thesis will be done in the framework of scientific collaboration between LAMIH UMR CNRS 8201 - Polytechnic University of Hauts-de-France (UPHF), France and Faculty of Science, University of Lisbon, Portugal. The student will be co-supervised by Francisco Saldanha da Gama (University of Lisbon) and Raca Todosijevic (LAMIH, UPHF). Required competences: - Master degree in Operations Research / Mathematics / Computers Science or equivalent; - Strong knowledge in operations research including metaheuristics and mathematical programming; - Knowledge in stochastic optimization and/or optimization under uncertainty is a plus; - Excellent programming skills (e.g., C/C++, C#, Python, Java); - Knowledge of optimization software (CPLEX, GUROBI, GAMS, BARON etc) is a plus; - A high degree of autonomy and commitment to work; - Strong written and verbal communication skills in English; - Knowledge of French and Portuguese languages are not necessary. Duration: 3 years Salary: around 1450 euros net per month. The candidate will have possibility of teaching at UPHF, which is paid extra. Application: All candidates should send their applications by e-mail to the below contacts. Application must contain: CV, motivation letter, two or more recommendation letters, copies of most recent diplomas along with exam marks. Any other document that may strengthen candidate’s application is welcome. Contacts: Francisco Saldanha da Gama, University of Lisbon, Portugal Email: fsgama(a)ciencias.ulisboa.pt Raca Todosijevic LAMIH UMR CNRS 8201 – Polytechnic University of Hauts-de-France, France Email: racatodosijevic(a)gmail.com , racatodosijevic(a)uphf.fr ______________________________________________________________________________ Francisco Saldanha da Gama, PhD Departamento de Estatística e Investigação Operacional Centro de Matemática, Aplicações Fundamentais e Investigação Operacional Faculty of Science, University of Lisbon, Portugal Phone: +351 217 500 019 | Fax: +351 217500081 | E-mail: fsgama(a)ciencias.ulisboa.pt<mailto:fsgama@fc.ul.pt> http://webpages.fc.ul.pt/~faconceicao www.deio.fc.ul.pt<http://www.deio.fc.ul.pt/> | www.fc.ul.pt<http://www.fc.ul.pt/> | http://www.fc.ul.pt/en/unidade/cmafcio Coordinator of the Undergraduate Program in Applied Mathematics https://fenix.ciencias.ulisboa.pt/degrees/matematica-aplicada-5645004366153… Editor-in-Chief Computers & Operations Research http://www.journals.elsevier.com/computers-and-operations-research

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MESS 2020 ~ Learning & Optimization from Big Data ~ Catania, 27-31 July 2020
by Mario Pavone 11 Feb '20

11 Feb '20

Call for Participation (apologies for multiple copies) ----------------------------------------------------------------------- MESS 2020 - Metaheuristics Summer School - Learning & Optimization from Big Data - 27-31 July 2020, Catania, Italy https://www.ANTs-lab.it/mess2020/ mess.school(a)ANTs-lab.it https://www.facebook.com/groups/MetaheuristicsSchool/ ----------------------------------------------------------------------- *** ONCE MONTH LEFT!!! *** ** APPLICATION DEADLINE: 5th March 2020 ** https://www.ants-lab.it/mess2020/application/ MESS 2020 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. All 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. Participants will be delivered a certificate of attendance indicating the number of hours of lectures (36-40 hours of lectures). In according to the academic system all PhD and master students attending to the summer school will may get 8 ECTS points. ** LIST OF LECTURERS + Angelo Cangelosi, University of Manchester & Alan Turing Institute, UK + Swagatam Das, Indian Statistical Institute, Kolkata + Luca Maria Gambardella, IDSIA Istituto Dalle Molle for Artificial Intelligence, Switzerland + Salvatore Greco, University of Catania, Italy & University of Portsmouth, UK + Emma Hart, Edinburgh Napier University, UK + Mauricio Resende, AMAZON, USA + Roman Slowinski, Pozna? University of Technology, Poland + El-Ghazali Talbi, University of Lille 1, France + Daniele Vigo, University of Bologna, Italy More Lecturers will be announced soon. ** SCHOOL DIRECTORS + Pascal Bouvry, University of Luxembourg, Luxembourg + Salvatore Greco, University of Catania, Italy + Ender Ozcan, University of Nottingham, UK + Mario Pavone, University of Catania, Italy + El-Ghazali Talbi, University of Lille 1, France + Daniele Vigo, University of Bologna, Italy ** METAHEURISTICS COMPETITION All participants to the school will be involved in the ?Metaheuristics Competition?, where each of them will must develop a metaheuristic solution on the given problem. The top three of the competition ranking will receive the MESS 2020 prize. Students whose algorithm will rank in the first 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. ** METAHEURISTICS COMPETITION CHAIRS + Raffaele Cerulli, University of Salerno, Italy + Andrea Schaerf, University of Udine, Italy ** SHORT TALK & POSTER PRESENTATION All participants may submit an abstract of their recent results, or works in progress, for presentation and having the opportunities for debate and interact with leaders in the field. Mini-Workshop Organizers and Scientific Committee will review the abstracts and will recommend for the format of the presentation (oral or poster). All abstracts will be published on the electronic hands-out book of the summer school. The Abstracts must be submitted by *March 5, 2020*. ** WORKSHOP CHAIRS + Vincenzo Cutello, University of Catania, Italy + Paola Festa, University of Naples ?Federico II?, Italy + Isaac Triguero, University of Nottingham, UK *See Previous Edition - MESS 2018* https://www.ants-lab.it/mess2018/ ** MORE INFORMATION: https://www.ANTs-lab.it/mess2020/ -- mess.school(a)ANTs-lab.it Facebook Group: https://www.facebook.com/groups/MetaheuristicsSchool/ Twitter: https://twitter.com/MESS_school

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Associate Professor position in Transportation and Logistics in Nantes, France
by Fabien Lehuédé 10 Feb '20

10 Feb '20

IMT Atlantique is recruiting an Associate Professor in Optimization and AI for Transportation and Logistics in Nantes, France. The selected candidate will join the SLP or TASC team of the Nantes research laboratory in Computer Science (https://www.ls2n.fr/?lang=en). For further information, please see https://partage.imt.fr/index.php/s/8gXRDwY9wB79kCX -- Fabien LEHUÉDÉ - fabien.lehuede(a)imt-atlantique.fr Professor, Head of the Logistics and Production group, IMT Atlantique, Laboratoire des Sciences du Numérique de Nantes (LS2N) +332 51 85 83 21 La Chantrerie 4 rue Alfred Kastler BP 20722 44307 Nantes Cedex 3, France

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ENOG February 2020