The GECCO 2016 Industrial Applications & EC in Practice Day is dedicated to the discussion of issues related to practical applications of Evolutionary Computation. During one day (Wednesday July 20, 2016), the most relevant topics related to real-world applications are discussed from various perspectives.
It is a great forum for meeting the leading experts in this important field.
This day starts with the “Industrial Applications of Metaheuristics” workshop, followed by two “Evolutionary Computation in Practice” sessions. A panel discussion with experts concludes this day.
Program
Wednesday July 20, 2016
Workshop: Industrial Applications of Metaheuristics (IAM)
Chair: Thomas Stützle
Metaheuristics have been applied successfully to many aspects of applied mathematics and science, showing their capabilities to deal effectively with problems that are complex and otherwise difficult to solve. There are a number of factors that make the usage of metaheuristics in industrial applications more and more interesting. These factors include the flexibility of these techniques, the increased availability of high-performing algorithmic techniques, the increased knowledge of their particular strengths and weaknesses, the ever increasing computing power, and the adoption of computational methods in applications. In fact, metaheuristics have become a powerful tool to solve a large number of real-life optimization problems in different fields and, of course, also in many industrial applications such as production scheduling, distribution planning, and inventory management.
This workshop proposes to present and debate about the current achievements of applying these techniques to solve real-world problems in industry and the future challenges, focusing on the (always) critical step from the laboratory to the shop floor. A special focus will be given to the discussion of which elements can be transferred from academic research to industrial applications and how industrial applications may open new ideas and directions for academic research.
Wednesday July 20, 2016
10:40am-12:30pm
• 10:40 Thomas Bartz-Beielstein: “Surrogate Model-based Optimization in Practice”
• 11:15 Maizura Mokhtar, Ian Hunt, Stephen Burns and Dave Ross: “Optimising a Waste Heat Recovery System using Multi-Objective Evolutionary Algorithm”
• 11:30 Erik Hemberg, Ignacio Arnaldo and Una-May O’Reilly: “Multi-Line Batch Scheduling by Similarity”
• 11:45 Abdel-Rahman Hedar, Majid Almaraashi and Alaa Abdel-Hakim: “Granular-Based Dimension Reduction for Solar Radiation Prediction Using Adaptive Memory Programming”
• 12:00 Silvino Fernández, Pablo Valledor, Diego Díaz, Eneko Malatsetxebarria and Miguel Iglesias: “Criticality of Response Time in the usage of Metaheuristics in Industry”
• 12:15 Silvino Fernández, Pablo Valledor: “System demonstration, ArcelorMittal Scheduling and Tuning suite“
Track: Evolutionary Computation in Practice (ECiP)
Chairs: Anna Esparcia Alcazar, Thomas Bartz-Beielstein, Erik Goodman
In the Evolutionary Computation in Practice (ECiP) track, well-known speakers with outstanding reputation in academia and industry present background and insider information on how to establish reliable cooperation with industrial partners. They actually run companies or are involved in cooperations between academia and industry.
If you attend, you will learn multiple ways to extend EC practice beyond the approaches found in textbooks. Experts in real-world optimization with decades of experience share their approaches to creating successful projects for real-world clients. Some of what they do is based on sound project management principles, and some is specific to our type of optimization projects. In this session a panel of experts describes a range of techniques you can use to identify, design, manage, and successfully complete an EA project for a client.
If you are working in academia and are interested in managing industrial projects, you will receive valuable hints for your own research projects.
Wednesday July 20, 2016
2:00pm-3:50pm
Session I
• 2:00 Bogdan Filipic: “Challenges of Deploying Evolutionary Computation in Steel Industry”
• 2:30 Carlos A. Coello Coello: “Evolutionary Multi-Objective Optimization in Real- World Applications”
• 3:55 Anna Esparcia Alcazar: “EC in industry: the quest for the Holy Grail – from Brain Computer Interfaces to automated testing with TESTAR”
• 3:20 Michael Affenzeller: “Heuristic Optimization in Production and Logistics”
Wednesday July 20, 2016
4:10pm-6:00pm
Session II
• 4:10 Thomas Bäck: “Intelligent Industry Solutions”
• 4:40 Felipe Campelo: “EAs for aeronautical optimization – some results and challenges”
• 5:10 Erik Goodman: “How to Introduce Academic-developed EC Technology to Industry”
• 5:40 Anna Esparcia Alcazar, Thomas Bäck, Thomas Bartz-Beielstein, Felipe Campelo, Silvino Fernández, Erik Goodman, Thomas Stützle:
“Panel Discussion”
A panel of experts with decades of real-world application experience will be answering questions posed by attendees of the sessions. We expect interesting discussions related – but not only restricted – to the following topics:
1) Industrial problems that lie on the cutting edge of EA development. This session gives you the opportunity to get free consulting from the experts.
2) Getting a job with training in evolutionary computation can be much easier if you know the things to do and the things not to do in your last year or two of study. You will hear from a panel of experts who have trained students and who have hired students to carry out real-world optimization. Highly recommended if you will be looking for a job in the next few years – or if you are thinking of changing jobs.
Speakers’ Bios
Michael Affenzeller obtained his PhD in Computer Science in 2001.
His Genetic Algorithms Research Group was founded in 2002. In 2004 he received his Habilitation in “Applied Systems Sciences with particular regard to Heuristic Optimization” at the Johannes Kepler University Linz, Austria. From 2004 – 2005 he was Assistant Professor at the Institute of Formal Models and Verification at the Johannes Kepler University Linz, Austria. Since 11/2005, he is a Professor for Applied Computer Science at the Department of Software Engineering of the Upper Austrian University of Applied Sciences in Hagenberg, Austria. From 2008-2013 he was Head of the Josef Ressel Center for Heuristic Optimization (Heureka!). Since 2014 he is Head of the K Project for Heuristic Optimization in Production and Logistics, Head of the Master Degree Program for Software Engineering, and Vice dean for R&D.
More: http://heal.heuristiclab.com/team/affenzeller
Thomas Bäck is full professor of computer science at the Leiden Institute of Advanced Computer Science (LIACS), Leiden University, The Netherlands, since 2004. He received his PhD in Computer Science (under supervision of Hans-Paul Schwefel) from Dortmund University, Germany, in 1994, and then worked for the Informatik Centrum Dortmund (ICD) as department leader of the Center for Applied Systems Analysis. From 2000 – 2009, Thomas was President of NuTech Solutions GmbH and CTO of NuTech Solutions, Inc. In 2009, he founded divis intelligent solutions GmbH. The company provides data mining and optimization software and services to customers such as BMW, Daimler, Ford, Honda, and many others. Thomas Bäck has more than 200 publications as well as a book on evolutionary algorithms, entitled Evolutionary Algorithms: Theory and Practice, and is co-editor of the Handbook of Evolutionary Computation and the Handbook of Natural Computing, and co-author of the book Contemporary Evolution Strategies (Springer, 2013). He is editorial board member of a number of journals and has served as program chair for major conferences in evolutionary computation. He received the best dissertation award from the Gesellschaft für Informatik (GI) in 1995 and is an elected fellow of the International Society for Genetic and Evolutionary Computation for his contributions to the field. Thomas Bäck received the IEEE CIS Evolutionary Computation Pioneer Award 2015 for his contributions in synthesizing evolutionary computation.
More: http://natcomp.liacs.nl
Thomas Bartz-Beielstein: Since 2006, when he became a professor for Applied Mathematics at TH Köln, Thomas has built a research team of international status and visibility. He is head of the research center Computational Intelligence plus (www.ciplus-research.de), and head of the SPOTSeven Lab at TH Köln (www.spotseven.de). His expertise lies in optimization, simulation, and statistical analysis of complex real-world problems. He is one of the leaders in the field of statistical analysis of optimization algorithms and the inventor and the driving force behind the sequential parameter optimization technology (SPOT). Thomas has more than 100 publications on computational intelligence, optimization, simulation, and experimental research. His books on experimental research are considered as milestones in this emerging field. Thomas serves as program chair for all major conferences in computational intelligence as well as a reviewer for several scientific institutions, e.g., Dutch National Science Foundation, Natural Sciences and Engineering Research Council of Canada, Academy of Finland, and Federal Ministry of Education and Research Germany. In addition, Thomas serves as a reviewer for leading journals in the field of Computational Intelligence, Optimization, and Simulation. Thomas is shareholder of Bartz & Bartz GmbH (http://www.bartzundbartz.de).
More: https://www.th-koeln.de/personen/thomas.bartz-beielstein/
Felipe Campelo is a professor of Optimization and Computational Intelligence with the Department of Electrical Engineering at Universidade Federal de Minas Gerais (UFMG), Brazil. He obtained his degree in Electrical Engineering from UFMG in 2003, and received both his M.Sc. (Information Science and Technology, 2006) and PhD (Systems Science and Informatics, 2009) from Hokkaido University, Japan, with a thesis on applied topology and parameter optimization of electromagnetic devices using evolutionary approaches. He has been directly involved with UFMG’s undergraduate courses on Systems Engineering and Aerospace Engineering, and with the Graduate Program in Electrical Engineering, where his lectures on Statistical Design and Analysis of Experiments have attracted hundreds of students over the last five years. His current research interests involve the development of experimental frameworks for algorithmic research, statistical modeling of the dynamics of evolutionary algorithms, effective approaches for preference-guided multi/many-objective optimization, and the deployment of statistical modeling and optimization heuristics to the solution of applied engineering problems. Felipe is a co-founder of the Operations Research and Complex Systems Laboratory (ORCS Lab, UFMG). He is also currently serving his second term as Deputy Head of UFMG’s Department of Electrical Engineering.
More: http://orcslab.cpdee.ufmg.br/index.php/faculty/5-felipe-campelo
Carlos Artemio Coello Coello received a PhD in Computer Science from Tulane University (USA) in 1996. He is currently full professor with distinction at CINVESTAV-IPN in Mexico City, Mexico. He has published over 380 papers in international peer-reviewed journals, book chapters, and conferences. He has also co-authored the book Evolutionary Algorithms for Solving Multi-Objective Problems,which is now in its Second Edition (Springer, 2007) and has co-edited the book Applications of Multi-Objective Evolutionary Algorithms (World Scientific, 2004). His publications currently report over 23,000 citations, according to Google Scholar (his h-index is 61). He received the 2007 National Research Award (granted by the Mexican Academy of Science) in the area of exact sciences and, since January 2011, he is an IEEE Fellow for “contributions to multi-objective optimization and constraint-handling techniques.” He is also the recipient of the prestigious 2013 IEEE Kiyo Tomiyasu Award and of the 2012 National Medal of Science and Arts in the area of Physical, Mathematical and Natural Sciences (this is the highest award that a scientist can receive in Mexico). He also serves as associate editor of the journals Evolutionary Computation, IEEE Transactions on Evolutionary Computation, Computational Optimization and Applications and Applied Soft Computing.
More: http://delta.cs.cinvestav.mx/~ccoello/
Anna Esparcia-Alcázar: Born in Valencia (Spain), Anna Esparcia-Alcázar obtained a degree in Ingenieria Industrial from the Universidad Politecnica de Valencia. After working as a lecturer in Control Engineering at the Departamento de Ingeniería de Sistemas, Computadores y Automática (currently DISA), in 1995 she joined the Department of Electronics and Electrical Engineering of the University of Glasgow, where she obtained a PhD (Thesis: “Genetic Programming for Adaptive Digital Signal Processing”) and also worked as a Research Assistant.
In 1998 Dr. Esparcia-Alcázar joined the Industrial Control Centre at the University of Strathclyde as a Research Fellow working on the CONVEX project, a joint project with the University of Glasgow, British Aerospace and Stirling Dynamics Ltd.
From January 2000 till August 2002 she worked for Barcelona-based GTD- Ingenieria de Sistemas y Software Industrial, Advanced Logistics Group and Pivetal Sistemas.
From September 2002 till September 2010 Dr. Esparcia-Alcázar was with the Instituto Tecnológico de Informática (ITI) at the Universidad Politécnica de València, where she was Coordinator of the Complex Adaptive Systems Group. From October 2010 till October 2011 she was Associate Lecturer at the Department of Systems Engineering and Automation (DISA) at the Universidad Politecnica de Valencia.
From October 2010 to March 2015 she was Head of R&D at S2 Grupo, where she was the Technical Manager and Coordinator of FP7 project MUSES, (October 2012 -September 2015).
Since May 2015 she is with the Software Production Methods Centre (PROS) of the Universidad Politecnica de Valencia.
She is Senior Member of the IEEE and elect member of the Executive Committee of SIGEVO, the Special Interest Group of the ACM on Genetic and Evolutionary Computation. In April 2015 she received the Award for Outstanding Contribution in Evolutionary Computation.
More: https://sites.google.com/site/aiesparcia/
Silvino Fernández is a R&D Engineer at the Global R&D Department of ArcelorMittal for more than 11 years. He develops his activity in the ArcelorMittal R&D Centre of Asturias, in the framework of the Business and TechnoEconomic project Area. He has a Master Science degree in Computer Science, obtained at University of Oviedo in Spain, and also a Ph.D. in Engineering Project Management obtained in 2015. His main research interests are in analytics, metaheuristics and swarm intelligence, and he has broad experience in using these kind of techniques in industrial environment to optimize production processes.
More: http://www.arcelormittal.com/
Bogdan Filipic is a senior researcher and head of Computational Intelligence Group at the Department of Intelligent Systems of the Jozef Stefan Institute, Ljubljana, Slovenia, and associate professor of Computer Science at the Jozef Stefan International Postgraduate School and at the University of Ljubljana. He is an expert in stochastic optimization, evolutionary computation and intelligent data analysis. Recently he has been focusing on parallelization, use of surrogate models and visualization of results in evolutionary multiobjective optimization. He is also active in promoting evolutionary computation in practice and has led optimization projects for steel production, car manufacturing and energy distribution. He co-chaired the biennial BIOMA conference from 2004 to 2012, and served as the general chair of PPSN 2014. He was a guest lecturer at the VU University Amsterdam, The Netherlands, in Fall 2014, and was giving tutorials on industrial applications of evolutionary algorithms at WCCI 2014 and CEC 2015.
More: http://dis.ijs.si/filipic/
Erik Goodman: At Michigan State University, Erik Goodman is a professor of Electrical and Computer Engineering and of Mechanical Engineering and of Computer Science and Engineering. He is the director of BEACON: An NSF Center for the Study of Evolution in Action, headquartered at MSU (see article below and the brand new BEACON site at http://beacon-center.org/ . He also co-direct MSU’s Genetic Algorithms Research and Applications Group (GARAGe), which is administered jointly by the Department of Electrical and Computer Engineering and the Department of Computer Science and Engineering. In February, 2007, he was awarded the university’s highest teaching award, the Alumni Club of Mid-Michigan Quality in Undergraduate Teaching Award, followed in 2009 by the Michigan Distinguished Professor of the Year Award. He is founder of Red Cedar Technology, Inc. and also involved in information and communications technology research and outreach in Africa.
More: http://www.egr.msu.edu/~goodman/
Thomas Stützle is a senior research associate of the Belgian F.R.S.-FNRS working at the IRIDIA laboratory of Université libre de Bruxelles (ULB), Belgium. He received the Diplom (German equivalent of M.S. degree) in business engineering from the Universität Karlsruhe (TH), Karlsruhe, Germany in 1994, and his PhD and his habilitation in computer science both from the Computer Science Department of Technische Universität Darmstadt, Germany, in 1998 and 2004, respectively. He is the co-author of two books about Stochastic Local Search: Foundations and Applications andAnt Colony Optimization and he has extensively published in the wider area of metaheuristics including 20 edited proceedings or books, 8 journal special issues, and more than 190 journal, conference articles and book chapters, many of which are highly cited. He is associate editor of Computational Intelligence, Swarm Intelligence, and Applied Mathematics and Computation and on the editorial board of seven other journals including Evolutionary Computation and Journal of Artificial Intelligence Research. His main research interests are in metaheuristics, swarm intelligence, methodologies for engineering stochastic local search algorithms, multi-objective optimization, and automatic algorithm configuration. In fact, since more than a decade he is interested in automatic algorithm configuration and design methodologies and he has contributed to some effective algorithm configuration techniques such as F-race, Iterated F-race and ParamILS. His 2002 GECCO paper on “A Racing Algorithm For Configuring Metaheuristics” (joint work with M. Birattari, L. Paquete, and K. Varrentrapp) has received the 2012 SIGEVO impact award.
More: http://iridia.ulb.ac.be/~stuetzle/
GECCO 2016
Industrial Applications &
Evolutionary Computation in Practice Day
Wednesday July 20, 2016
Room: Mesa Verde A
More: http://gecco-2016.sigevo.org/index.html/EC+in+Practice