7 papers · 1 filter
On the Structural (Dis)Agreement of Landscape Representations in Black-Box Optimization
Sara Gjorgjieva, Eva Tuba, Barbara KorouÅ¡iÄ Seljak +2
Landscape feature representations play a central role in automated algorithm selection and meta-learning for black-box optimization, yet little is known about how different represe…
Quantifying the Impact of Modules and Their Interactions in the PSO-X Framework
Christian L. Camacho-Villalón, Ana Nikolikj, Katharina Dost +3
The PSO-X framework incorporates dozens of modules that have been proposed for solving single-objective continuous optimization problems using particle swarm optimization. While mo…
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…
Tracing the Interactions of Modular CMA-ES Configurations Across Problem Landscapes
Ana Nikolikj, Mario Andrés Muñoz, Eva Tuba +1
This paper leverages the recently introduced concept of algorithm footprints to investigate the interplay between algorithm configurations and problem characteristics. Performance…
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…
Customized Exploration of Landscape Features Driving Multi-Objective Combinatorial Optimization Performance
Ana Nikolikj, Gabriela Ochoa, Tome Eftimov
We present an analysis of landscape features for predicting the performance of multi-objective combinatorial optimization algorithms. We consider features from the recently propose…