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 ...

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 ...

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 ...

• 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 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 ...

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 ...

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 ...

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 ...

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 ...