A self-adaptation of arbitrary normal mutation distributions within the concept of muta-tive strategy parameter control (MSC) using a newly formulated mutation operator is introduced. The coordinate system independent formulation ensures the invariance of the algorithm towards arbitrary linear transformations , which is a novelty for self-adaptation within the concept of MSC. To enable a sensib...

This paper points out how combined Genetic Programming techniques can be applied to the identification of nonlinear structures in experimental data. In many cases it is essential to generate an algebraic expression as a part of an equation that describes the physical representation of a dynamic system. Genetic Programming is an optimization procedure that can be used to identify such nonlinear ...

The CSA-ES is an Evolution Strategy with Cumulative Step size Adaptation, where the step size is adapted measuring the length of a so-called cumulative path. The cumulative path is a combination of the previous steps realized by the algorithm, where the importance of each step decreases with time. This article studies the CSA-ES on composites of strictly increasing functions with affine linear ...

A fundamental problem of modelling in Systems Biology is to precisely characterise quantitative parameters, which are hard to measure experimentally. For this reason, it is common practise to estimate these parameter values, using evolutionary and other techniques, by fitting the model behaviour to given data. In this contribution, we extensively investigate the influence of exponentially scale...

We describe the decomposition of QSO absorption line ensembles applying an evolutionary forward modelling technique. The modelling is optimized using an evolution strategy (ES) based on a novel concept of completely derandomized self-adaption. The algorithm is described in detail. Its global optimization performance in decomposing a series of simulated test spectra is compared to that of classi...

Human Group Optimization (HGO) algorithm, derived from the previously proposed seeker optimization algorithm (SOA), is a novel swarm intelligence algorithm by simulating human behaviors, especially human searching/foraging behaviors. In this paper, a canonical HGO with local search (L-HGO) is proposed. Based on the benchmark functions provided by CEC2005, the proposed algorithm is compared with...

In this work differential evolution strategies are applied in neural networks with integer weights training. These strategies have been introduced by Storn and Price [Journal of Global Optimization, 11, pp. 341–359, 1997]. Integer weight neural networks are better suited for hardware implementation as compared with their real weight analogous. Our intention is to give a broad picture of the beh...

An image registration approach based on Evolution Strategies is proposed. In image registration, an invariant reference needs to be established within each source image, which is unavailable in many cases. To solve this problem, feature configuration (which is defined as the cluster of feature vectors on an image representing homogeneous feature distribution,) is employed to describe the object...

According to the Efficient Market Hypothesis (EMH), a stock’s return is indifferent to a given trading day. But the day of the week effect phenomenon produces a different return for each day in the week. This is an abnormal return which can affect investors in deciding an investment strategy and portfolio management. This study examines the day of the week effect on stock market returns and the...

In recent years a lot of novel (mostly naturally inspired) search heuristics have been proposed. Among those approaches is Harmony Search. After its introduction in 2000, positive results and improvements over existing approaches have been reported. In this paper, the authors give a review of the developments of Harmony Search during the past decade and perform a rigorous analysis of this appro...