Oradores plenários/Plenary speakers

Alexandre Dolgui

Bernardo Almada-Lobo

António Murta

Alexandre Dolgui

Dr. Alexandre Dolgui is a Distinguished Professor (Full Professor of Exceptional Class in France) and the Head of Automation, Production and Computer Sciences Department at the IMT Atlantique (formerly Ecole des Mines de Nantes), France. His research focuses on manufacturing line design, production planning and supply chain optimization. His main results are based on the exact mathematical programming methods and their intelligent coupling with heuristics and metaheuristics algorithms. He is the co-author of 5 books, the co-editor of 16 books or conference proceedings, the author of more than 200 refereed journal papers, 25 editorials and 28 book chapters as well as over 400 papers in conference proceedings. He is the Editor-in-Chief of the International Journal of Production Research, an Area Editor of Computers & Industrial Engineering, and an Associate Editor of Journal Européen des Systèmes Automatisés, as well as member of the Editorial Boards for 25 other journals. He was General Scientific Chair of the 12th IFAC symposium INCOM'06, Chairman of International Program Committee of more than 10 international conferences and Chairman of Steering committee of MIM'16, and Member of Program Committees of over 200 International Conferences. He has been responsible of the French national CNRS working group on Design of Production Systems and the regional project on Design and Management of Reconfigurable Manufacturing Systems.

Combinatorial Design of Paced Production Lines in Machining Environment

A complex machine or machining line consists of a sequence of work positions through which products move one way in order to be processed. Designing such a production system represents a long-term decision problem involving different crucial decision stages. Combinatorial design is one of them; it mostly deals with assigning the set of indivisible units of work (named tasks or operations) to work positions (or stations). In literature, the most attention was paid for combinatorial design of assembly lines (assembly line balancing problems). In our work, we develop approaches and formulations of combinatorial design for machining lines and complex machines.

In this talk, a brief survey of our results on combinatorial design of complex machines and machining lines is presented. This deals not only with assigning tasks to a sequence of linearly ordered workstations, but necessitate also to solve jointly some other decision problems, such as process planning, equipment selection, configuration design or task sequencing. Making simultaneously different decisions can reach better final line performance and effectiveness. Advanced operational research techniques are used, a decision aid software is developed and applied in the automotive industry.

Bernardo Almada-Lobo

Associate Professor with Habilitation at the Industrial Engineering and Management Department of Faculty of Engineering of Porto University. Member of the Board at INESC TEC Technology and Science. Co-founder of LTPlabs (spin-off of INESC-TEC). Member of the Board of Trustees of Fundação Belmiro de Azevedo.
Certified Analytics Professional from The Institute for Operations Research and the Management Sciences. His main area of activity is Management Science/Operations Research. He develops and applies advanced analytical models and methods to help make better decisions, solving managerial problems in various domains (manufacturing, health, retail and mobility), with a special focus on Operations Management.

Boosting the Practice of Prescriptive Analytics

Most organizations already use effectively descriptive analytics to understand past events. Fewer attempts are observed in the domain of predictive analytics to anticipate scenarios and estimate, and only a minority of the firms leverages intelligent recommendations based on prescriptive analytics.

The necessary change of the mindset of companies regarding the use of optimization models and business decision support systems, requires more than just appropriate technology, people and processes. It demands a proper change management.

In this talk, we make use of a few successful and unsuccessful business analytics projects, as well as recent developments in prescriptive analytics, to draw some guidelines and best practices to address this challenge.

António Murta

António is Managing Partner, co-founder and CEO of Pathena. Also, António serves as a non-exec board member of two companies of Pathena's portfolio, and is observer in the board of other portfolio companies.
António has a degree in systems engineering from Minho University, an MBA from Porto Business School (University of Porto), an AMP from INSEAD (France). Has also done post-graduate studies at ISEE/ University of Navarra (Spain) and MIT (Sloan School of Management US) and Singularity University (US) – Exponential Medicine.
From 1991 to 1997 he was corporate information officer of Sonae Distribuição, the largest Portuguese retailer. He founded and was CEO of Enabler from 1998 onwards – Enabler was a systems integrator strictly focused in retail. Enabler was acquired by Wipro in 2006 and from then to the end of 2009 he was VP of retail services at Wipro.
He is also a Founding Partner and business angel of various other IT and MedTech companies. António is the Co-Chairman of the fund-raising committee of University of Minho, Advisory Board Member of School of Nursing of the University of Minho, Advisory Board Member of INL, Advisory Board Member of INESC Porto, Member of Advisory Council of Grupo Mello Corporate Program Grow, Member of Medical Degree Evaluation Committee in Medical School of University of Minho and Member of the Strategic Council of VdA, Vieira de Almeida Sociedade de Advogados. He is also a seasoned speaker in innovation and entrepreneurship.

From OR to AI – with ML on the way