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Plenary Speaker

 

Automated Algorithm Configuration: Methods, Applications and Prospects

Thomas Stützle
IRIDIA, Université Libre de Bruxelles (ULB), Belgium.

 


Abstract:

The design and configuration of effective optimization algorithms for computationally hard problems is a time-consuming, difficult algorithm engineering task. This is in large part due to a number of aggravating circumstances such as the NP-hardness of most of the problems to be solved, the difficulty of algorithm analysis due to stochasticity and heuristic biases, and the large number of degrees of freedom in defining and selecting algorithmic components and settings of numerical parameters. Over the recent years, the development of automatic methods to search large configuration spaces has received significant attention as a possible solution to these challenges. Such automatic algorithm configuration methods have by now proved to be instrumental for developing high-performance algorithms.

The presentation will discuss how automatic algorithm configuration tools can be used to develop high-performing evolutionary and other optimization algorithms. After an overview of available tools, I will highlight various successful applications of these such as the automatic configuration of multi-objective optimizers and the improvement of the anytime behavior of optimization algorithms. Finally, I will highlight the impact automatic algorithm configuration has and will have on the algorithm design and development process.

 

Biography:

Dr. Stützle is a tenured researcher of the Belgian F.R.S.-FNRS working at the IRIDIA laboratory of Université libre de Bruxelles (ULB), Belgium. He received an M.S. in business engineering from the Universität Karlsruhe (TH), Germany in 1994, and his PhD and his habilitation in computer science both from the computer science department of Technische Universität Darmstadt, Germany. He is the co-author of two books about “Stochastic Local Search: Foundations and Applications” and “Ant Colony Optimization,” both being the main references in their respective areas. His main research interests are in metaheuristics, swarm intelligence, methodologies for engineering stochastic local search algorithms, multi-objective optimization, and the automatic configuration of algorithms.

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