Justin Gan

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This paper describes the recent developments and improvements made to the variable radius niching technique called Dynamic Niche Clustering (DNC) originally described in [4] and [5]. DNC employs a separate population of overlapping fuzzy niches with independent radii which operate in the decoded parameter space and are maintained alongside the normal GA(More)
In this paper, a continuation of a variable radius niche technique called Dynamic Niche Clustering developed by (Gan & Warwick, 1999) is presented. The technique employs a separate dynamic population of overlapping niches that coexists alongside the normal population. An empirical analysis of the updated methodology on a large group of standard optimisation(More)
Genetic algorithm's (GA's) have become a powerful search tool pertaining to the identification of global optima within multimodal domains. Many different methodologies and techniques have been developed to aid in this search, and facilitate the efficient location of these optima. What has become known as Goldberg's standard fitness sharing methodology is(More)
– We present here some additions to a fuzzy variable radius niche technique called Dynamic Niche Clustering (DNC) [3, 4 & 5] that enable the identification and creation of niches of arbitrary shape through a mechanism called Niche Linkage. We show that by using this mechanism it is possible to attain better feature extraction from the underlying population.(More)
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