Browsing by Author "Caraffini, Fabio"
Now showing items 1-20 of 39
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Algorithmic issues in computational intelligence optimization: from design to implementation, from implementation to design
Caraffini, Fabio (Thesis)The vertiginous technological growth of the last decades has generated a variety of powerful and complex systems. By embedding within modern hardware devices sophisticated software, they allow the solution of complicated ... -
Application of uninorms to market basket analysis
Moodley, Raymond; Chiclana, Francisco; Caraffini, Fabio; Carter, Jenny (Article)The ability for grocery retailers to have a single view of customers across all their grocery purchases remains elusive and has become increasingly important in recent years (especially in the UK) where competition has ... -
Cluster-Based Population Initialization for differential evolution frameworks
Poikolainen, Ilpo.; Neri, Ferrante; Caraffini, Fabio (Article)Abstract This article proposes a procedure to perform an intelligent initialization for population-based algorithms. The proposed pre-processing procedure, namely Cluster-Based Population Initialization (CBPI) consists of ... -
Collaborative research and sharing data ahead of paper publication: A case study of De Montfort University’s Dr. Fabio Caraffini
Caraffini, Fabio; Hardeman, M. (Other)• By sharing his high-resolution, multispectral images prior to a paper publication on DMU Figshare, Fabio and his colleagues are building public engagement with their research. • Storing large amounts of data in DMU ... -
Compact differential evolution light: high performance despite limited memory requirement and modest computational overhead
Iacca, Giovanni; Caraffini, Fabio; Neri, Ferrante (Article)Compact algorithms are Estimation of Distribution Algorithms which mimic the behavior of population-based algorithms by means of a probabilistic representation of the population of candidate solutions. These algorithms ... -
Compact Optimization Algorithms with Re-sampled Inheritance
Iacca, Giovanni; Caraffini, Fabio (Conference)Compact optimization algorithms are a class of Estimation of Distribution Algorithms (EDAs) characterized by extremely limited memory requirements (hence they are called \compact"). As all EDAs, compact algorithms build ... -
A comparison of three Differential Evolution strategies in terms of early convergence with different population sizes
Yaman, Anil; Iacca, Giovanni; Caraffini, Fabio (Conference)Differential Evolution (DE) is a popular population-based continuous optimization algorithm that generates new candidate solutions by perturbing the existing ones, using scaled differences of randomly selected solutions ... -
Continuous Parameter Pools in Ensemble Differential Evolution
Iacca, Giovanni; Caraffini, Fabio; Neri, Ferrante (Conference)Ensemble of parameters and mutation strategies differential evolution (EPSDE) is an elegant promising optimization framework based on the idea that a pool of mutation and crossover strategies along, with associated pools ... -
A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms
The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the ... -
HyperSPAM: A study on hyper-heuristic coordination strategies in the continuous domain
Caraffini, Fabio; Neri, Ferrante; Epitropakis, Michael G. (Article)This article proposes a simplistic algorithmic framework, namely hyperSPAM, composed of three search algorithms for addressing continuous optimisation problems. The Covariance Matrix Adaptation Evolution Strategy (CMAES) ... -
The Importance of Being Structured: a Comparative Study on Multi Stage Memetic Approaches
Caraffini, Fabio; Iacca, Giovanni; Neri, Ferrante; Mininno, Ernesto (Conference)Memetic Computing (MC) is a discipline which studies optimization algorithms and sees them as structures of operators, the memes. Although the choice of memes is crucial for an effective algorithmic design, special attention ... -
Improving (1+1) Covariance Matrix Adaptation Evolution Strategy: a simple yet efficient approach
Caraffini, Fabio; Iacca, Giovanni; Yaman, Anil (Conference)In recent years, part of the meta-heuristic optimisation research community has called for a simplification of the algorithmic design: indeed, while most of the state-of-the-art algorithms are characterised by a high level ... -
Infeasibility and structural bias in Differential Evolution
Caraffini, Fabio; Kononova, Anna V.; Corne, David (Article)Structural bias is a recently identified property of optimisation algorithms, causing them to favour certain regions of the search space over others, independently of the objective function. Since structural bias can ... -
Large Scale Problems in Practice: The effect of dimensionality on the interaction among variables
Caraffini, Fabio; Neri, Ferrante; Iacca, Giovanni (Conference)This article performs a study on correlation between pairs of variables in dependence on the problem dimensionality. Two tests, based on Pearson and Spearman coefficients, have been designed and used in this work. In total, ... -
Meta-Lamarckian learning in three stage optimal memetic exploration
Neri, Ferrante; Weber, Matthieu; Poikolainen, Ilpo; Caraffini, Fabio (Conference)Three Stage Optimal Memetic Exploration (3SOME) is a single-solution optimization algorithm where the coordinated action of three distinct operators progressively perturb the solution in order to progress towards the ...