This paper presents EDACluster, an Estimation of Distribution Algorithm (EDA) applied to the clustering task. EDA is an Evolutionary Algorithm used here to optimize the search for adequate clusters when very little is known about the target dataset. The proposed algorithm uses a mixed approach – density and grid-based – to identify sets of dense cells in the dataset. The output is a list of ite...

A critical part of the design of eeective EAs is to obtain a proper balance between exploration and exploitation. A key element of this balance is the selection algorithm used. Although we have for some time now understood the relative diierences between various selection methods for standard centralized EAs, our understanding of decentralized EAs has been less complete. In this paper we presen...

Since the various clustering methods developed over the time have failed to prove their flawless efficiency in the field, it might be that evolutionary computation holds the solution to this issue as well. The goal of this paper is to present such an evolutionary technique with a classical clustering engine behind it.

Background: Stearoyl-CoA desaturase (SCD) is a key enzyme that converts saturated fatty acids (SFAs) to monounsaturated fatty acids (MUFAs) in fat biosynthesis. Despite being crucial for interpreting SCDs’ roles across species, the evolutionary relationship of SCD proteins across species has yet to be elucidated. This study aims to present this evolutionary relationship based on amino aci...

A novel methodology for unsupervised data clustering based on Evolutionary Computation, named “Intelligent Unsupervised Clustering” (IUC) is introduced. IUC searches for the “optimal clusters’ representatives” using Evolutionary Algorithms (EAs) and utilising a Window Density Function (WDF) as an objective function. EAs ensure that the representative is posed in a region of points of high densi...

Evolutionary computation techniques have received a lot of attention regarding their potential as optimization techniques for complex numerical functions. However, they have not produced a signi cant breakthrough in the area of nonlinear programming due to the fact that they have not addressed the issue of constraints in a systematic way. Only recently several methods have been proposed for han...

One of the major components of any evolutionary system is the evaluation function. Evaluation functions are used to assign a quality measure for individuals in a population. Whereas evolutionary computation techniques assume the existence of an (e cient) evaluation function for feasible individuals, there is no uniform methodology for handling (i.e., evaluating) unfeasible ones. The simplest ap...

A low energy clustering method of body area networks based on fuzzy simulated evolutionary computation is proposed in this paper. To reduce communication energy consumption, we also designed a fuzzy controller to dynamically adjust the crossover and mutation probability. Simulations are conducted by using the proposed method, the clustering methods based on the particle swarm optimization and t...