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A comparison of localised and global niching methods
Niching methods are a useful extension of evolutionary computation that allow evolutionary algorithms to be applied in multimodal problem domains. Current niching methods use either one of two methods to promote the formation ...
Discovering population structures with extreme fixation rates via evolutionary search
Genetic drift is a well known and important force in directing the evolution of a population. The nature of genetic drift in panmictic populations is well understood, and new research is shedding light on the behaviour of ...
Evolutionary multiobjective optimisation through spatially-structured non-dominated sorting: a preliminary study
Multiobjective evolutionary algorithms (MOEAs) are useful tools capable of searching problems that contain several conflicting criteria. Although MOEAs have been shown to be capable of finding a wide spread of Pareto-optimal ...
Fixation of neutral alleles in spatially structured populations via genetic Drift: Describing the spatial structure of faster-than-panmictic configurations
This paper considers spatially-structured populations described as a network, and examines the properties of these networks in terms of their affect on fixation of neutral alleles due solely to genetic drift. Individuals ...
How does space alter the formulation of evolutionary models?
This short paper discusses how space is introduced within evolutionary models and reviews several approaches from the literature. In particular, the Moran process is used as one type of model that has been described in ...
A Voronoi-based distributed genetic algorithm
The use of space for supporting evolution has been previously studied in the context of distributed Genetic Algorithms (DGA), where two standard approaches, island and grid based, are employed to define the population ...
The emergence and distribution of species in a gradient-based spatially-structured evolutionary algorithm
The ability to discover and maintain multiple solutions within a single run is a desirable property for evolutionary algorithms. Researchers have previously turned to many biologically-inspired methods for inspiration to ...
An empirical investigation into correlation functions in a spatially-dispersed evolutionary algorithm
Spatially-structured populations play an important role in controlling selection pressure in evolutionary algorithms. The imposing space on a evolving population has traditionally been biased toward the underlying architecture ...
An explicit spatial model for niching in genetic algorithms
A niching technique is an important component of the genetic algorithm when attempting to solve problems that have multiple optimal solutions. Traditional niching techniques use an explicit concept of similarity to perform ...