Project-Team Randopt
Team, Visitors, External Collaborators
Overall Objectives
Scientific Context
Overall Objectives
Research Program
Introduction
Developing Novel Theoretical Frameworks for Analyzing and Designing Adaptive Stochastic Algorithms
Algorithmic developments
Setting novel standards in scientific experimentation and benchmarking
Application Domains
Application Domains
Highlights of the Year
New Software and Platforms
COCO
CMA-ES
New Results
A multiobjective algorithm framework and the COMO-CMA-ES algorithm
A mixed-integer benchmark testbed for single and multiobjective black-box optimization
A large-scale optimization testbed for the COCO framework
Diagonal Acceleration for Covariance Matrix Adaptation Evolution Strategies
A global surrogate assisted CMA-ES
Benchmarking and Understanding Optimizers
Bilateral Contracts and Grants with Industry
Bilateral Contracts with Industry
Partnerships and Cooperations
Regional Initiatives
National Initiatives
International Initiatives
International Research Visitors
Dissemination
Promoting Scientific Activities
Teaching - Supervision - Juries
Popularization
Bibliography
Publications of the year
References in notes
Inria
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Raweb 2019
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Presentation of the Project-Team RANDOPT
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RANDOPT Web Site
PDF
e-Pub
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Section: Partnerships and Cooperations
Regional Initiatives
PGMO/FMJH project “AESOP: Algorithms for Expensive Simulation-Based Optimization”, 7kEUR, 2017–2019
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