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    Browsing by Author "Caraffini, Fabio"

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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 ...
      • An analysis on separability for Memetic Computing automatic design 

        Caraffini, Fabio; Neri, Ferrante; Picinali, Lorenzo (Article)
      • 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 ...
      • Can compact optimisation algorithms be structurally biased? 

        Kononova, Anna V.; Caraffini, Fabio; Wang, Hao; Bäck, Thomas (Conference)
        In the field of stochastic optimisation, the so-called structural bias constitutes an undesired behaviour of an algorithm that is unable to explore the search space to a uniform extent. In this paper, we investigate whether ...
      • Can Single Solution Optimisation Methods Be Structurally Biased? 

        Kononova, Anna V.; Caraffini, Fabio; Wang, Hao; Back, Thomas (Article)
        This paper investigates whether optimisation methods with the population made up of one solution can suffer from structural bias just like their multisolution variants. Following recent results highlighting the importance ...
      • 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 ...
      • A Clustering System for Dynamic Data Streams Based on Metaheuristic Optimisation 

        Yeoh, Jia Ming; Caraffini, Fabio; Santucci, Valentino; Milani, Alfredo; Homapour, E. (Article)
        This article presents the Optimised Stream clustering algorithm (OpStream), a novel approach to cluster dynamic data streams. The proposed system displays desirable features, such as a low number of parameters and good ...
      • A CMA-ES Super-fit Scheme for the Re-sampled Inheritance Search 

        Caraffini, Fabio; Iacca, Giovanni; Neri, Ferrante; Picinali, Lorenzo; Mininno, Ernesto (Conference)
      • 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 ...
      • Cooperative and distributed decision-making in a multi-agent perception system for improvised land mines detection 

        Florez-Lozano, Johana; Caraffini, Fabio; Parra, Carlos; Gongora, Mario Augusto (Article)
        This work presents a novel intelligent system designed using a multi-agent hardware platform to detect improvised explosive devices concealed in the ground. Each agent is equipped with a different sensor, (i.e. a ...
      • A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms 

        Iacca, Giovanni; Neri, Ferrante; Caraffini, Fabio; Suganthan, Ponnuthurai Nagaratnam (Conference)
        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 ...
      • Efficient Computation of the Nonlinear Schrödinger Equation with Time-Dependent Coefficients 

        Kosti, Athinoula; Colreavy-Donnelly, S.; Caraffini, Fabio; Anastassi, Zacharias (Article)
        Motivated by the limited work performed on the development of computational techniques for solving the nonlinear Schrödinger equation with time-dependent coefficients, we develop a modified Runge-Kutta pair with improved ...
      • An experimental study of prediction methods in robust optimization over time 

        Fox, Matthew; Yang, Shengxiang; Caraffini, Fabio (Conference)
        Robust Optimization Over Time (ROOT) is a new method of solving Dynamic Optimization Problems in respect to choosing a robust solution, that would last over a number of environment changes, rather than the approach that ...
      • Focusing the search: A progressively shrinking memetic computing framework 

        Poikolainen, I.; Iacca, Giovanni; Caraffini, Fabio; Neri, Ferrante (Conference)
      • Handling Non-Separability in Three Stage Memetic Exploration 

        Poikolainen, Ilpo; Caraffini, Fabio; Neri, Ferrante; Weber, Matthieu (Conference)
      • 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) ...

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