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GERAD seminar

Learning variable neighborhood search for a job-scheduling problem


Jun 21, 2019   10:30 AM — 11:30 AM

Nicolas Zufferey Full Professor, GSEM, University of Geneva, Switzerland

Variable neighborhood search is a local search metaheuristic that uses sequentially different neighborhood structures. This method has been successfully applied to various types of problems. In this work, variable neighborhood search is enhanced with a learning mechanism which helps to drive the search toward promising areas of the search space. The resulting method is applied to a single-machine scheduling problem with rejections, setups, and earliness and tardiness penalties. Experiments are conducted for instances from the literature. They show on the one hand the benefit of the learning mechanism (in terms of solution quality and robustness). On the other hand, the proposed method significantly outperforms state-of-the-art algorithms for the considered problem. Moreover, its flexibility allows its straightforward adaptation to other combinatorial optimization problems.

Free entrance.
Welcome to everyone!


Room 4488
André-Aisenstadt Building
Université de Montréal Campus
2920, chemin de la Tour
Montréal QC H3T 1J4

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