Evolutionary algorithms applied to dynamic optimization problems has become a promising research area. So far, all papers in the area have assumed that the environment changes only between generations. In this paper, we take a first look at possibilities to handle a change during a generation. For that purpose, we derive an analytical model for a (1, 2) evolution strategy and show that sometime...

This paper reports on novel work using clonal selection (CS) for dynamic function optimisation. A comparison is made between evolution strategies (ES) and CS, for the optimisation of two significantly different dynamic functions at 2, 5 and 10 dimensions. Firstly a sensitivity analysis was performed for both the CS and the ES for both fitness functions. Secondly the performance of the two algor...

The ridge function class is a parameterised family of test functions that is often used to evaluate the capabilities and limitations of optimisation strategies. Past research with the goal of analytically determining the performance of evolution strategies on the ridge has focused either on the parabolic case or on simple one-parent strategies without step length adaptation. This paper extends ...

With rising importance of knowledge interchange, many industrial and academic applications have adopted ontologies as their conceptual backbone. However, industrial and academic environments are very dynamic, thus inducing changes to application requirements. To fulfill these changes, often the underlying ontology must be evolved as well. As ontologies grow in size, the complexity of change man...

The paper presents an approach to the acquisition of texture models of specific objects under the following assumptions: (I) the system has to recognize objects on a sequence of images. (2) images of a sequence demonstrate the variability of conditions under which objects are perceived (e.g., resolution. lighting, surface positioning), (3) an observer or objects can move, (4) the extraction of ...

This paper presents the N-dependent analysis of the (1;) Evolution Strategy (ES) with isotropic mutations at the ridge functions including the special cases sharp and parabolic ridge. The new approach presented allows for the prediction of the dynamics in ridge direction as well as in radial direction. The central quantities are the corresponding progress rates which are determined in terms of ...

Background: Protein Kinase A (PKA) is confined to subcellular compartments by A-Kinase Anchoring Proteins (AKAPs) Results: A structure-based phage directed evolution strategy has yielded modified type II PKA regulatory subunits with AKAP-selective binding properties Conclusion: Engineered RSelect proteins preferentially target particular AKAP-PKA interfaces Significance: RSelect subunits are to...

Similar to Genetic Algorithms, Evolution Strategies (ESs) are algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems. The development of Evolution Strategies from the rst mutation{selection scheme to the reened (,){ES including the general concept of self{adaptation of the strategy parameters for the mutation variances as well as their ...

Biological evolution gives rise to self-organizing phenomena. Inspired by this theory, directed variation is added to the ( , ) evolution strategies (ES) algorithm and it is called directed variation ES (DVES). In DVES, some neighboring individuals in the population mutate correlatively according to the distribution of the whole population. Experimental results showed that, with the same number...

This study aims at supplementing the empirical basis of using software evolution evaluation methods in industrial settings. An industrial case study applying Value-Based Decision Model (VDM) for software evolution strategy evaluations is presented. VDM considers the value of a legacy software system and proposes convenient evolution strategies. Use of VDM is characterized, and the case study de...