Real-world optimization problems have been comparatively difficult to solve due to the
complex nature of the objective function with a substantial number of constraints. To deal …

In the power and energy systems area, a progressive increase of literature contributions that
contain applications of metaheuristic algorithms is occurring. In many cases, these …

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 …

Benchmarking plays an important role in the development of novel search algorithms as well
as for the assessment and comparison of contemporary algorithmic ideas. This paper …

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

To develop new meta-heuristic algorithms and evaluate on the benchmark functions is the
most challenging task. In this paper, performance of the various developed meta-heuristic …

The steady supply of new optimization methods makes the algorithm selection problem
(ASP) an increasingly pressing and challenging task, specially for real-world black-box …

The popularity of metaheuristics, especially Swarm Intelligence and Evolutionary Algorithms,
has increased rapidly over the last two decades. Numerous algorithms are proposed each …

Bayesian optimization (BO) with Gaussian processes (GPs) surrogate models is widely used
to optimize analytically unknown and expensive-to-evaluate functions. In this paper, we …

Various benchmark sets have already been proposed to facilitate comparison between
metaheuristics, or Evolutionary Algorithms. During the competition, typically algorithms are …