4 papers
ClustOpt: A Clustering-based Approach for Representing and Visualizing the Search Dynamics of Numerical Metaheuristic Optimization Algorithms
Gjorgjina Cenikj, Gašper Petelin, Tome Eftimov
Understanding the behavior of numerical metaheuristic optimization algorithms is critical for advancing their development and application. Traditional visualization techniques, suc…
Comparing Optimization Algorithms Through the Lens of Search Behavior Analysis
Gjorgjina Cenikj, Gašper Petelin, Tome Eftimov
The field of numerical optimization has recently seen a surge in the development of "novel" metaheuristic algorithms, inspired by metaphors derived from natural or human-made proce…
The Pitfalls of Benchmarking in Algorithm Selection: What We Are Getting Wrong
Gašper Petelin, Gjorgjina Cenikj
Algorithm selection, aiming to identify the best algorithm for a given problem, plays a pivotal role in continuous black-box optimization. A common approach involves representing o…
A Survey of Features Used for Representing Black-box Single-objective Continuous Optimization
Gjorgjina Cenikj, Ana Nikolikj, Gašper Petelin +3
This survey examines key advancements in designing features to represent optimization problem instances, algorithm instances, and their interactions within the context of single-ob…