104 citations · 366 across the 10 of their papers we have counts for
10 papers
An investigation on the use of Large Language Models for hyperparameter tuning in Evolutionary Algorithms
Leonardo Lucio Custode, Fabio Caraffini, Anil Yaman +1
Hyperparameter optimization is a crucial problem in Evolutionary Computation. In fact, the values of the hyperparameters directly impact the trajectory taken by the optimization pr…
Direct deduction of chemical class from NMR spectra
Stefan Kuhn, Carlos Cobas, Agustin Barba +3
This paper presents a proof-of-concept method for classifying chemical compounds directly from NMR data without doing structure elucidation. This can help to reduce time in finding…
Emergence of Structural Bias in Differential Evolution
Bas van Stein, Fabio Caraffini, Anna V. Kononova
Heuristic optimisation algorithms are in high demand due to the overwhelming amount of complex optimisation problems that need to be solved. The complexity of these problems is wel…
Is there Anisotropy in Structural Bias?
Diederick Vermetten, Anna V. Kononova, Fabio Caraffini +2
Structural Bias (SB) is an important type of algorithmic deficiency within iterative optimisation heuristics. However, methods for detecting structural bias have not yet fully matu…
Training Data Set Assessment for Decision-Making in a Multiagent Landmine Detection Platform
Johana Florez-Lozano, Fabio Caraffini, Carlos Parra +1
Real-world problems such as landmine detection require multiple sources of information to reduce the uncertainty of decision-making. A novel approach to solve these problems includ…
Differential evolution outside the box
Anna V. Kononova, Fabio Caraffini, Thomas Bäck
This paper investigates how often the popular configurations of Differential Evolution generate solutions outside the feasible domain. Following previous publications in the field,…
Infeasibility and structural bias in Differential Evolution
Fabio Caraffini, Anna V. Kononova, David Corne
This paper thoroughly investigates a range of popular DE configurations to identify components responsible for the emergence of structural bias - recently identified tendency of th…
Multi-Strategy Coevolving Aging Particle Optimization
Giovanni Iacca, Fabio Caraffini, Ferrante Neri
We propose Multi-Strategy Coevolving Aging Particles (MS-CAP), a novel population-based algorithm for black-box optimization. In a memetic fashion, MS-CAP combines two components w…
Compact Optimization Algorithms with Re-sampled Inheritance
Giovanni Iacca, Fabio Caraffini
Compact optimization algorithms are a class of Estimation of Distribution Algorithms (EDAs) characterized by extremely limited memory requirements (hence they are called "compact")…
Structural bias in population-based algorithms
Anna V. Kononova, David W. Corne, Philippe De Wilde +2
Challenging optimisation problems are abundant in all areas of science. Since the 1950s, scientists have developed ever-diversifying families of black box optimisation algorithms d…