Webpage: https://sites.google.com/view/iam-workshop/home
Description
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.
As in the previous edition, the workshop together with the rest of the conference will be held in a hybrid mode promoting the participation.
Topic areas of IAM 2025 include (but are not restricted to):
• Success stories for industrial applications of metaheuristics
• Pitfalls of industrial applications of metaheuristics.
• Metaheuristics to optimize dynamic industrial problems.
• Multi-objective optimization in real-world industrial problems.
• Meta-heuristics in very constraint industrial optimization problems: assuring feasibility, constraint-handling techniques.
• Reduction of computing times through parameter tuning and surrogate modelling.
• Parallelism and/or distributed design to accelerate computations.
• Algorithm selection and configuration for complex problem solving.
• Advantages and disadvantages of metaheuristics when compared to other techniques such as integer programming or constraint programming.
• New research topics for academic research inspired by real (algorithmic) needs in industrial applications.
Submission
Authors can submit short contributions including position papers of up to 4 pages and regular contributions of up to 8 pages following in each category the GECCO paper formatting guidelines. Software demonstrations will also be welcome.
The submission deadlines will adhere to the standard GECCO schedule for workshops.
The workshop itself will be publicized through mailing lists and academic and industrial contacts of the organizers.
Submissions from industry will be especially welcome.
Organizers
Silvino Fernández Alzueta
He is Senior Scientist in Mathematical Optimization at the Global R&D Division of ArcelorMittal with an experience of more than 15 years working in innovative projects applying Evolutionary Computation in real problems. He develops his activity in the ArcelorMittal R&D Centre of Asturias (Spain), in the framework of the Mathematical Optimization team, as part of the Digital Direction. His has a Master Science degree in Computer Science and a Ph.D. in Engineering Project Management, both obtained at University of Oviedo in Spain. His main research interests are in analytics, metaheuristics and swarm intelligence, and he has broad experience in using these techniques in industrial environment to optimize production processes. His paper "Scheduling a Galvanizing Line by Ant Colony Optimization" obtained the best paper award in the ANTS conference in 2014.
He is a research engineer of the Global R&D Asturias Centre at ArcelorMittal (world's leading integrated steel and mining company), working at the Business & Technoeconomic department. He obtained his MS degree in Computer Science in 2006 and his PhD on Business Management in 2015, both from the University of Oviedo. He worked for the R&D department of CTIC Foundation (Centre for the Development of Information and Communication Technologies in Asturias) until February 2007, when he joined ArcelorMittal. His main research interests are metaheuristics, multi-objective optimization, analytics and operations research.
Thomas Stützle is a research director of the Belgian F.R.S.-FNRS working at the IRIDIA laboratory of Université libre de Bruxelles (ULB), Belgium. He received 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 and ``Ant Colony Optimization and he has extensively published in the wider area of metaheuristics including 22 edited proceedings or books, 11 journal special issues, and more than 250 journal, conference articles and book chapters, many of which are highly cited. He is associate editor of Computational Intelligence, Evolutionary Computation and Applied Mathematics and Computation and on the editorial board of seven other journals. 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.