Comparing parameter tuning methods for evolutionary algorithms

Abstract — Tuning the parameters of an evolutionary algorithm (EA) to a given problem at hand is essential for good algorithm performance. Optimizing parameter values is, however, a non-trivial problem, beyond the limits of human problem solving.In this light it is odd that no parameter tuning algorithms are used widely in evolutionary computing. This paper is meant to be stepping stone towards a better practice by discussing the most important issues related to tuning EA parameters, describing a number of existing tuning methods, and presenting a modest experimental comparison among them. The paper is concluded by suggestions for future research – hopefully inspiring fellow researchers for further work. Index Terms — evolutionary algorithms, parameter tuning I. BACKGROUND AND OBJECTIVES Evolutionary Algorithms (EA) form a rich class of stochasti

Costs and benefits of tuning parameters of evolutionary algorithms

Abstract. We present an empirical study on the impact of different design choices on the performance of an evolutionary algorithm (EA). Four EA components are considered—parent selection, survivor selection, recombination and mutation—and for each component we study the impact of choosing the right operator and of tuning its free parameter(s). We tune 120 different combinations of EA operators to 4 different classes of fitness landscapes and measure the cost of tuning. We find that components differ greatly in importance. Typically the choice of operator for parent selection has the greatest impact, and mutation needs the most tuning. Regarding individual EAs however, the impact of design choices for one component depends on the choices for other components, as well as on the available amount of resources for tuning.

Predicting polarization enhancement in multicomponent ferroelectric superlattices

Ab initio calculations are utilized as an input to develop a simple model of polarization in epitaxial short-period CaTiO3/SrTiO3/BaTiO3 superlattices grown on a SrTiO3 substrate. The model is then combined with a genetic algorithm technique to optimize the arrangement of individual CaTiO3, SrTiO3 and BaTiO3 layers in a superlattice, predicting structures with the highest possible polarization and a low in-plane lattice constant mismatch with the substrate. This modelling procedure can be applied to a wide range of layered perovskite-oxide nanostructures providing guidance for experimental development of nanoelectromechanical devices with substantially improved polar properties.Comment: 4 pages, submitted to PR

Prevention and control of apple scab

Improved prevention and control of apple scab caused by Venturia inaequalis is aimed at without the use of copper containing products in the Repco-project. Substantial progress is made in selection of potential products against summer epidemics. A patent application is made for E73. New effective biocontrol agents are selected to reduce inoculum during winter. The product potassium bicarbonate has shown good efficacy and Repco contributes to the registration of this product in Europe. Earthworms tended to be stimulated to consume apple leaves treated with amino acids or beetpulp, especially when applied fresh under controlled environmental condi-tons