The Pareto Differential Evolution (PDE) algorithm was introduced last year and showed competitive results. The behavior of PDE, as in many other evolutionary multiobjective optimization (EMO) methods, varies according to the crossover and mutation rates. In this paper, we present a new version of PDE with self-adaptive crossover and mutation. We call the new version Self–adaptive Pareto Differe...

1 We consider a population that adapts to a gradually changing environment. Our 2 aim is to describe how ecological and genetic factors combine to determine the genetic 3 basis of adaptation. Specifically, we consider the evolution of a polygenic trait that is 4 under stabilizing selection with a moving optimum. The ecological dynamics is defined 5 by the strength of selection, σ̃, and the speed...

Mutator genotypes with increased mutation rates may be especially important in microbial evolution if genetic adaptation is generally limited by the supply of mutations. In experimental populations of the bacterium Escherichia coli, the rate of evolutionary adaptation was proportional to the mutation supply rate only in particular circumstances of small or initially well-adapted populations. Th...

We are interested in modelling Darwinian evolution, resulting from the interplay of phenotypic variation and natural selection through ecological interactions. Our models are rooted in the microscopic, stochastic description of a population of discrete individuals characterized by one or several adaptive traits. The population is modelled as a stochastic point process whose generator captures t...

Adaptive (or stationary-phase) mutation is a group of phenomena in which mutations appear to occur more often when selected than when not. They may represent cellular responses to the environment in which the genome is altered to allow survival. The best-characterized assay system and mechanism is reversion of a lac allele on an F' sex plasmid in Escherichia coli, in which the stationary-phase ...

Microbial populations under nonlethal selection can give rise to mutations that relieve the selective pressure, a phenomenon that has come to be called "adaptive mutation." One explanation for adaptive mutation is that a small proportion of the cells experience a period of transient hypermutation, and that these hypermutators account for the mutations that appear. The experiments reported here ...

Abstract Genetic programming (GP) automatically designs programs. Evolutionary (EP) is a real-valued global optimisation method. EP uses probability distribution as mutation operator, such Gaussian, Cauchy, or Lévy distribution. This study proposes hyper-heuristic approach that employs GP to design different operators for EP. At each generation, the algorithm can adaptively explore search space...

Is senescence the adaptive result of tradeoffs between younger and older ages or the nonadaptive burden of deleterious mutations that act at older ages? To shed new light on this unresolved question we combine adaptive and nonadaptive processes in a single model. Our model uses Penna's bit-strings to capture different age-specific mutational patterns. Each pattern represents a genotype and for ...

The biological theory of adaptive dynamics proposes a description of the long-term evolution of a structured asexual population. It is based on the assumptions of large population, rare mutations and small mutation steps, that lead to a deterministic ODE describing the evolution of the dominant type, called the ‘canonical equation of adaptive dynamics’. Here, in order to include the effect of s...

Many evolutionary studies assume that deleterious mutations necessarily impede adaptive evolution. However, a later mutation that is conditionally beneficial may interact with a deleterious predecessor before it is eliminated, thereby providing access to adaptations that might otherwise be inaccessible. It is unknown whether such sign-epistatic recoveries are inconsequential events or an import...