Search results for "algorithm"
showing 10 items of 4887 documents
A hybrid genetic algorithm with local search
2001
Abstract A hybrid genetic algorithm with internal local search was developed for optimisations involving continuous variables. The reproduction probabilities were enhanced using the fitness values obtained when a local method was applied to each individual in the population. These estimations are more realistic, since consider not the apparent but the hidden, latent quality of each individual. The information gathered in the local search was also used to build an auxiliary population recording the successfully enhanced individuals, which allowed to detect the convergence and self-adapt the search limits. The size of this auxiliary population was kept constant by a cluster analysis strategy.…
The inheritance of organogenic response in melon
1996
Previous studies have demonstrated variation in organogenic competence among plants within a population ofCucumis melo. In order to determine if leaf explant response is under genetic control, we investigated the distribution of the shoot regeneration frequency in F1 and F2 generations from parents representing extreme values forin vitro organogenic response. Results suggest a genetic model with two genes, partial dominance, independent segregation and similar effects for both genes.
Selection on life-history traits and genetic population divergence in rotifers
2009
A combination of founder effects and local adaptation – the Monopolization hypothesis – has been proposed to reconcile the strong population differentiation of zooplankton dwelling in ponds and lakes and their high dispersal abilities. The role genetic drift plays in genetic differentiation of zooplankton is well documented, but the impact of natural selection has received less attention. Here, we compare differentiation in neutral genetic markers (FST) and in quantitative traits (QST) in six natural populations of the rotifer Brachionus plicatilis to assess the importance of natural selection in explaining genetic differentiation of life-history traits. Five life-history traits were measur…
Memetic Compact Differential Evolution for Cartesian Robot Control
2010
This article deals with optimization problems to be solved in the absence of a full power computer device. The goal is to solve a complex optimization problem by using a control card related to portable devices, e.g. for the control of commercial robots. In order to handle this class of optimization problems, a novel Memetic Computing approach is presented. The proposed algorithm employs a Differential Evolution framework which instead of processing an actual population of candidate solutions, makes use of a statistical representation of the population which evolves over time. In addition, the framework uses a stochastic local search algorithm which attempts to enhance the performance of th…
Factors influencing the extent of inbreeding depression: an example from scots pine
1999
Detailed studies suggest that the level of inbreeding depression may vary between populations. In a study of Scots pine from Finland, the level of inbreeding depression was much lower in northern than in southern populations. We have examined theoretically whether population genetic factors, such as the level of selfing, intensity of selection against heterozygotes or homozygotes, level of mutation, a bottleneck, finite population size, or the level of polyembryony could account for this difference. Higher selfing or stronger selection against heterozygotes in the north, both at biologically reasonable levels, appear to produce changes consistent with the observed differences and we conside…
An analysis of the bias of variation operators of estimation of distribution programming
2018
Estimation of distribution programming (EDP) replaces standard GP variation operators with sampling from a learned probability model. To ensure a minimum amount of variation in a population, EDP adds random noise to the probabilities of random variables. This paper studies the bias of EDP's variation operator by performing random walks. The results indicate that the complexity of the EDP model is high since the model is overfitting the parent solutions when no additional noise is being used. Adding only a low amount of noise leads to a strong bias towards small trees. The bias gets stronger with an increased amount of noise. Our findings do not support the hypothesis that sampling drift is …
Scratch detection and removal from static images using simple statistics and genetic algorithms
2002
This paper investigates the removal of line scratches from old movies and gives a twofold contribution. First, it presents simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, and it is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed with a conven…
Connections with Other Population-Based Approaches
2003
Throughout this book, we have established that scatter search (SS) belongs to the family of population-based metaheuristics. This family also includes the well-known evolutionary algorithms and the approach known as path relinking.
Diversity Management in Memetic Algorithms
2012
In Evolutionary Computing, Swarm Intelligence, and more generally, populationbased algorithms diversity plays a crucial role in the success of the optimization. Diversity is a property of a group of individuals which indicates how much these individuals are alike. Clearly, a group composed of individuals similar to each other is said to have a low diversity whilst a group of individuals dissimilar to each other is said to have a high diversity. In computer science, in the context of population-based algorithms the concept of diversity is more specific: the diversity of a population is a measure of the number of different solutions present, see [239].
A Primer on Memetic Algorithms
2012
Memetic Algorithms (MAs) are population-based metaheuristics composed of an evolutionary framework and a set of local search algorithms which are activated within the generation cycle of the external framework, see [376]. The earliest MA implementation has been given in [621] in the context of the Travelling Salesman Problem (TSP) while an early systematic definition has been presented in [615]. The concept of meme is borrowed from philosophy and is intended as the unit of cultural transmission. In other words, complex ideas can be decomposed into memes which propagate andmutate within a population.Culture, in this way, constantly undergoes evolution and tends towards progressive improvemen…