Instance Space Analysis (ISA) is a recently developed methodology to (a) support objective
testing of algorithms and (b) assess the diversity of test instances. Representing test …

It has long been observed that for practically any computational problem that has been
intensely studied, different instances are best solved using different algorithms. This is …

Fitness landscapes were proposed in 1932 as an abstract notion for understanding
biological evolution and were later used to explain evolutionary algorithm behaviour. The …

This survey compiles ideas and recommendations from more than a dozen researchers with
different backgrounds and from different institutes around the world. Promoting best practice …

The last decade has witnessed remarkable progress in the development of quantum
technologies. Although fault-tolerant devices likely remain years away, the noisy …

Over past few decades, as a powerful analytical tool to characterize the fitness landscape of
a problem, fitness landscape analysis (FLA) has been widely concerned and utilized for all …

Thirty years, 1993–2023, is a huge time frame in science. We address some major
developments in the field of evolutionary algorithms, with applications in parameter …

Literature is prolific with metaheuristics for solving continuous optimisation problems. But, in
practice, it is difficult to choose one appropriately for several reasons. First and …

Per-instance algorithm selection seeks to recommend, for a given problem instance and a
given performance criterion, one or several suitable algorithms that are expected to perform …

The herein proposed Python package pflacco provides a set of numerical features to
characterize single-objective continuous and constrained optimization problems. Thereby …