A new adaptive genetic algorithm using mutation matrix is introduced and implemented in a single computer using the quasi-parallel time sharing algorithm for the solution of the zero/one knapsack problem. The mutation matrix M(t) is constructed using the locus statistics and the fitness distribution in a population A(t) with N rows and L columns, where N is the size of the population and L is t...

Understanding the mechanisms of evolution requires identification of the molecular basis of the multiple (pleiotropic) effects of specific adaptive mutations. We have characterized the pleiotropic effects on protein levels of an adaptive single–base pair substitution in the coding sequence of a signaling pathway gene in the bacterium Pseudomonas fluorescens SBW25. We find 52 proteomic changes, ...

The classical model of adaptive evolution in an asexual population postulates that each adaptive clone is derived from the one preceding it1. However, experimental evidence has suggested more complex dynamics2–5, with theory predicting the fixation probability of a beneficial mutation as dependent on the mutation rate, population size and the mutation’s selection coefficient6. Clonal interferen...

While mutational biases strongly influence neutral molecular evolution, the role of mutational biases in shaping the course of adaptation is less clear. Here we consider the frequency of transitions relative to transversions among adaptive substitutions. Because mutation rates for transitions are higher than those for transversions, if mutational biases influence the dynamics of adaptation, the...

The JFH1 strain of hepatitis C virus (HCV) is unique among HCV isolates, in that the wild-type virus can traverse the entire replication cycle in cultured cells. However, without adaptive mutations, only low levels of infectious virus are produced. In the present study, the effects of five mutations that were selected during serial passage in Huh-7.5 cells were studied. Recombinant genomes cont...

The use and potential benefits of self-adaptive mutation operators are well-known within evolutionary computing. In this paper we begin by examining the use of self-adaptive mutation in Learning Classifier Systems. We implement the operator in the simple ZCS classifier and examine its performance in two maze environments. It is shown that, although no significant increase in performance is seen...

The dynamics of populations evolving on an adaptive landscape depends on multiple factors, including the structure of the landscape, the rate of mutations, and effective population size. Existing theoretical work often makes ad hoc and simplifying assumptions about landscape structure, whereas experimental work can vary important parameters only to a limited extent. We here overcome some of the...

Differential Evolution (DE) is a simple, yet highly competitive real parameter optimizer in the family of evolutionary algorithms. A significant contribution of its robust performance is attributed to its control parameters, and mutation strategy employed, proper settings of which, generally lead to good solutions. Finding the best parameters for a given problem through the trial and error meth...

We present two dynamical models for the appearance of adaptive mutations, which permit a quantitative comparison with experimental observations. The models quantify two alternative pictures: The hyper-mutating sub-population picture, and the population-wide mutation picture. We 3nd that both models are equally successful in reproducing the results of experiments in which a single mutation is re...

Abstract The problem of finding roots equations has always been an important research in the fields scientific and engineering calculations. For standard differential evolution algorithm cannot balance convergence speed accuracy solution, improved is proposed. First, one-half rule introduced mutation process, that is, half individuals perform evolutionary mutation, other strategy reorganization...