An insight into bio-inspired and evolutionary algorithms for global optimization: review, analysis, and lessons learnt over a decade of competitions
Over the recent years, continuous optimization has significantly evolved to become the
mature research field it is nowadays. Through this process, evolutionary algorithms had an …
mature research field it is nowadays. Through this process, evolutionary algorithms had an …
Large scale global optimization: Experimental results with MOS-based hybrid algorithms
Continuous optimization is one of the most active research Iines in evolutionary and
metaheuristic algorithms. Through CEC 2005 to CEC 2013 competitions, many different …
metaheuristic algorithms. Through CEC 2005 to CEC 2013 competitions, many different …
Benchmarking feature-based algorithm selection systems for black-box numerical optimization
R Tanabe - IEEE Transactions on Evolutionary Computation, 2022 - ieeexplore.ieee.org
Feature-based algorithm selection aims to automatically find the best one from a portfolio of
optimization algorithms on an unseen problem based on its landscape features. Feature …
optimization algorithms on an unseen problem based on its landscape features. Feature …
Multiple offspring sampling in large scale global optimization
Continuous optimization is one of the most active research lines in evolutionary and
metaheuristic algorithms. Through CEC 2005 to CEC 2011 competitions, many different …
metaheuristic algorithms. Through CEC 2005 to CEC 2011 competitions, many different …
Surrogate-assisted evolutionary algorithms
I Loshchilov - 2013 - theses.hal.science
Evolutionary Algorithms (EAs) have received a lot of attention regarding their potential to
solve complex optimization problems using problem-specific variation operators. A search …
solve complex optimization problems using problem-specific variation operators. A search …
Machine learning based multiscale calibration of mesoscopic constitutive models for composite materials: application to brain white matter
A modular pipeline for improving the constitutive modelling of composite materials is
proposed. The method is leveraged here for the development of subject-specific spatially …
proposed. The method is leveraged here for the development of subject-specific spatially …
Benchmarking a hybrid DE-RHC algorithm on real world problems
Continuous optimization is one of the most active research lines in evolutionary and
metaheuristic algorithms. Through CEC 2005 to CEC 2010 competitions, many different …
metaheuristic algorithms. Through CEC 2005 to CEC 2010 competitions, many different …
SoftFEM: the soft finite element method
While the finite element method (FEM) has now reached full maturity both in academy and
industry, its use in optimization pipelines remains either computationally intensive or …
industry, its use in optimization pipelines remains either computationally intensive or …
Model calibration using a parallel differential evolution algorithm in computational neuroscience: Simulation of stretch induced nerve deficit
Neuronal damage, in the form of both brain and spinal cord injuries, is one of the major
causes of disability and death in young adults worldwide. One way to assess the direct …
causes of disability and death in young adults worldwide. One way to assess the direct …
BBOB 2009: Comparison tables of all algorithms on all noiseless functions
This document presents the results in the form of tables from the Black-Box Optimization
Benchmarking (BBOB) workshop of the Genetic and Evolutionary Computation Conference …
Benchmarking (BBOB) workshop of the Genetic and Evolutionary Computation Conference …