Analysis of the (μ/μI,λ)(\mu/\mu_I,\lambda)-CSA-ES with Repair by Projection Applied to a Conically Constrained Problem

Theoretical analyses of evolution strategies are indispensable for gaining a deep understanding of their inner workings. For constrained problems, rather simple problems are of interest in the current research. This work presents a theoretical analysis of a multi-recombinative evolution strategy with cumulative step size adaptation applied to a conically constrained linear optimization problem. The state of the strategy is modeled by random variables and a stochastic iterative mapping is introduced. For the analytical treatment, fluctuations are neglected and the mean value iterative system is considered. Non-linear difference equations are derived based on one-generation progress rates. Based on that, expressions for the steady state of the mean value iterative system are derived. By comparison with real algorithm runs, it is shown that for the considered assumptions, the theoretical derivations are able to predict the dynamics and the steady state values of the real runs.Comment: This is a PREPRINT of an article that has been accepted for publication in the journal MIT Press Evolutionary Computation (ECJ). 25 pages + supplementary material. The work was supported by the Austrian Science Fund FWF under grant P29651-N3

Self-Adaptive Genetic Algorithms with Simulated Binary Crossover

Self-adaptation is an essential feature of natural evolution. However, in the context of function optimization, self-adaptation features of evolutionary search algorithms have been explored only with evolution strategy (ES) and evolutionary programming (EP). In this paper, we demonstrate the self-adaptive feature of real-parameter genetic algorithms (GAs) using simulated binary crossover (SBX) operator and without any mutation operator. The connection between the working of self-adaptive ESs and real-parameter GAs with SBX operator is also discussed. Thereafter, the self-adaptive behavior of real-parameter GAs is demonstrated on a number of test problems commonly-used in the ES literature. The remarkable similarity in the working principle of real-parameter GAs and self-adaptive ESs shown in this study suggests the need of emphasizing further studies on self-adaptive GAs

Benchmarking Evolutionary Algorithms For Single Objective Real-valued Constrained Optimization - A Critical Review

Benchmarking plays an important role in the development of novel search algorithms as well as for the assessment and comparison of contemporary algorithmic ideas. This paper presents common principles that need to be taken into account when considering benchmarking problems for constrained optimization. Current benchmark environments for testing Evolutionary Algorithms are reviewed in the light of these principles. Along with this line, the reader is provided with an overview of the available problem domains in the field of constrained benchmarking. Hence, the review supports algorithms developers with information about the merits and demerits of the available frameworks.Comment: This manuscript is a preprint version of an article published in Swarm and Evolutionary Computation, Elsevier, 2018. Number of pages: 4

Assessment of the method used to construct clearness index maps for the new european solar radiation atlas (ESRA).

International audienceWe present an assessement of the methods used to construct maps for a new Solar Radiation Atlas for Europe. For this atlas station data and satellite derived data are used in an interpolation/merging process to derive maps of the long term monthly global radiation that cover an area ranging from 30° W to 70° E and from 25° to 75° N. Our focus is on the discussion of the accuracy of the method applied - a co-kriging technique. Special emphasis is put on the discussion whether the use of satellite derived radiation maps with a low spatial resolution brings benefits

Merging ground-measurements and satellite-derived data for the construction of global radiation map

International audienceThe European Commission is realizing the first digital European solar radiation atlas of the Greater Europe. Climatological maps of the global radiation available at ground are to be constructed. For that purpose, radiation data have been collected which have been measured at about 300 meteorological ground stations. These stations are mostly located in Western Europe and therefore any interpolation technique applied to these data will provide poor results outside this area. Radiation maps derived from satellite images are used as a constraint to the interpolation procedure (kriging), though they are less accurate than the ground measurements. This study shows that, compared to an interpolation of the ground measurements alone, merging satellite-derived maps and ground-based measurements improves the assessment of the global radiation in any geographical location which is not a ground station, and peculiarly for those far from any ground station. The relative error is a whole lower than 10 % and decreases down to a few percent when approaching a ground station