The field of parallel metaheuristics is continuously evolving as a result of new technologies
and needs that researchers have been encountering. In the last decade, new models of …

Any sufficiently complex system acts as a black box when it becomes easier to experiment
with than to understand. Hence, black-box optimization has become increasingly important …

We introduce COCO, an open-source platform for Comparing Continuous Optimizers in a
black-box setting. COCO aims at automatizing the tedious and repetitive task of …

This paper presents results of the BBOB-2009 benchmarking of 31 search algorithms on 24
noiseless functions in a black-box optimization scenario in continuous domain. The runtime …

Quantifying and comparing performance of optimization algorithms is one important aspect
of research in search and optimization. However, this task turns out to be tedious and difficult …

In this article, we build upon previous work on designing informative and efficient
Exploratory Landscape Analysis features for characterizing problems' landscapes and show …

Quantifying and comparing performance of optimization algorithms is one important aspect
of research in search and optimization. However, this task turns out to be tedious and difficult …

We propose a multistart CMA-ES with equal budgets for two interlaced restart strategies, one
with an increasing population size and one with varying small population sizes. This BI …

This book is the result of several years of research trying to better characterize parallel
genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. Readers …

For genetic algorithms, new variants of the uniform crossover operator that introduce
selective pressure on the recombination stage are proposed. Operator probabilistic rates …