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Evolutionary algorithms (EAs) are often well-suited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been develope...

We present an evolutionary algorithm that evolves a population of local approximators in order to fit an unknown function. The evolutionary algorithm performs a simultaneous learning of simple local approximators togethe...

In this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy wi...

The Open Shop Scheduling Problem (OSSP) is one of the most interesting, complexes and not frequently approached scheduling problems. Due to its intractability with other techniques, in this work we present an evolutionar...

In previous works the ability of CPS-MCPC (an evolutionary, co-operative, population search method with multiple crossovers per couple) to build well delineated Pareto fronts in diverse multiobjective optimization proble...

Multiobjective optimization, also known as vector-valued criteria or multicriteria optimization, have long been used in many application areas where a problem involves multiple objectives, often conflicting, to be met or...

The Estimation Distribution Algorithms (EDAs) compose an evolutionary metaheuristic whose main characteristic is the construction of solutions in randomly form, using a distribution of probabilities that evolves during t...

The Flow Shop Scheduling Problem have been tackled using different techniques which goes from mathematical techniques like Branch and Bound to metaheuristics like evolutionary algorithms (EAs). Although in the real worl...

Subjects / keywords: Artificial intelligence; Deep learning; Computer science; Artificial neural network; Backpropagation; Reinforcement learning; Machine learning; Deep neural networks; Unsupervised learning; Recurrent neural network; Encod...

Subjects / keywords: computational intelligence, artificial intelligence, machine learning, computer applications, distributed intelligent systems, evolutionary computation; Science: Mathematics: Instruments and machines: Electronic computer...

Subjects / keywords: artificial intelligence, machine learning, computer vision, computational intelligence, information engineering, evolutionary computation; Science: Mathematics: Instruments and machines: Electronic computers. Computer sc...

Subjects / keywords: intelligent systems, machine learning, neural computing, evolutionary computation, fuzzy systems, intelligent control and robotics; Science: Science (General): Cybernetics; Science: Mathematics: Instruments and machines:...

The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolut...

UNLABELLED: We have developed a new software package, Molecular Evolutionary Genetics Analysis version 2 (MEGA2), for exploring and analyzing aligned DNA or protein sequences from an evolutionary perspective. MEGA2 vastl...

We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been...

Subjects / keywords: Evolutionary biology; Human evolutionary genetics; Genetics; Biology; Molecular genetics; Computational biology; Genome; Gene

IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have con...

BACKGROUND: Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples. METHODS: To examine intratumor heterogen...

A mathematical model for the evolutionary change of restriction sites in mitochondrial DNA is developed. Formulas based on this model are presented for estimating the number of nucleotide substitutions between two popula...

The newest version of MUMmer easily handles comparisons of large eukaryotic genomes at varying evolutionary distances, as demonstrated by applications to multiple genomes. Two new graphical viewing tools provide alternat...

Subjects / keywords: Biology; Carcinogenesis; Colorectal cancer; Genetics; Computational biology; Evolutionary biology; Cancer research; Cancer

The fine detail provided by sequencing-based transcriptome surveys suggests that RNA-seq is likely to become the platform of choice for interrogating steady state RNA. In order to discover biologically important changes ...

Although much biological research depends upon species diagnoses, taxonomic expertise is collapsing. We are convinced that the sole prospect for a sustainable identification capability lies in the construction of systems...

Subjects / keywords: Computational biology; Evolutionary biology; Biology