Thematic Semester on Optimization

The CIMI Thematic Semester on Optimization deals with numerical optimization in a very general sense. Optimization is one of the internationally recognized research specialties in the city of Toulouse. It is strongly represented in various research institutes such as IRIT, IMT, LAAS or TSE. In addition, it is an important topic of the curriculum in local engineering schools and universities.

During this semester, we will tackle the modeling of real phenomena by optimization problems and their application to the resolution of concrete problems. This will lead us to examine almost all facets of optimization, ranging from continuous problems to discrete problems, convex or not, expressible analytically, or only in the form of "black box" or computable using long and complex simulations. A significant part of the semester is then dedicated to the design and analysis of algorithms (properties of algorithms, theoretical guarantees of convergence, notion of complexity).

The semester is divided into 5 main themes to cover almost all areas: large optimization, bio-inspired methods, discrete optimization, optimal control/EDO, and optimization for learning. An "ecumenical" math-business study week (SEME) covering all topics will be co-organized with LabEx AMIES and IRT Saint-Exupéry.

Events planned for 2018
June 4 - 5, 2018 Master Class on "Hybrid Methods for Combinatorial/Mixed Optimization".
June 27 - 29, 2018 Workshop "Optimization: fundamentals and algorithms for structured problems".
September 3 - 7, 2018 Spring School "Numerical Optimal Control".
September 10 - 13, 2018 Workshop "Optimization and Learning".
October 16-17, 2018 Workshop "Combinatorial Optimization and Learning".
October 18-19, 2018   Toulouse Symposium on Deep Learning
November 2018 Industrial workshop around Discrete optimization, Combinatorial optimization, Constraint programming.
 
Events planned for 2019
September 2019 SEME Optimization
September 2019 Neural Networks Days
October 2019 Artificial Evolution Conference (Artificial Evolution 2019)
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