| Classical test functions known as F1 to F10 are often used as a benchmark for heuristic optimisation techniques. Recently it has been remarked in literature that relying on the results obtained for their optimisation may be improper or even misleading to assess the eeciency of a technique with respect to others, and a method for developing new more reliable test functions has been given. In t...

The investigations in the paper have been carried out against the background of an integrated approach to the structural design problem. Due to the complex nature of the search space and the continous-discrete-binary system vector in the general case of structural optimization, conventional methods can not be used. Evolution strategies have shown their general capability to solve the sizing and...

Natural evolution is a population-based optimization process. Simulating this process on a computer results in stochastic optimization techniques that can often outperform classical methods of optimization when applied to difficult real-world problems. There are currently three main avenues of research in simulated evolution: genetic algorithms, evolution strategies, and evolutionary programmin...

This research proposes an automated OWL product domain ontology (PDO) evolution (without a human inspection) based on given user feedback and enhancing an existing ontology evolution concept. Its manual activities are eliminated by formulating an adaptation strategy for the conceptual aspects of an automated PDO evolution and establishing a feedback cycle. The adaptation strategy consists of a ...

Generally considered as the timely adaptation of ontologies to the changing requirements, ontology evolution is becoming more and more crucial as ontologies being widely used in different fields. In this paper, we intend to address the problem of evolving ontologies with less manual case-based reasoning using an automatic selection mechanism. We present an Automatic Ontology Evolution Strategy ...

The multi-recombinant (==;)-Evolution Strategy (ES) is investigated for real-valued, N-dimensional parameter spaces. The analysis includes the intermediate recombination and the dominant recombination as well. These investigations are done for the spherical model rst. The problem of the optimal population size depending on the parameter space dimension N is solved. A method extending the result...

This paper studies and describes two classes of local interaction Evolution Strategies (LES) where the choice of parents for mating as well as the decision for survival and replacement are performed locally only. The entire population is now considered to consist of spatially distributed individuals each belonging to its own overlapping neighborhood and selection operates on a set of local pool...

Evolution Strategies (ES) are a class of Evolutionary Algorithms based on Gaussian mutation and deterministic selection. Gaussian mutation captures pair-wise dependencies between the variables through a covariance matrix. Covariance Matrix Adaptation (CMA) is a method to update this covariance matrix. In this paper, the CMA-ES, which has found many applications in solving continuous optimizatio...

The cloud computing is considered as a computational model which provides the uses requests with resources upon any demand and needs.The need for planning the scheduling of the user's jobs has emerged as an important challenge in the field of cloud computing. It is mainly due to several reasons, including ever-increasing advancements of information technology and an increase of applications and...

Open Source Software (OSS) has become the subject of much commercial and academic interest of last. Providing quantitative metrics for OSS evolution has also become an urgent issue. However, most existing studies of software evolution have been performed on systems developed within a single company using traditional management techniques. These metrics models are not suitable for measuring OSS ...