Populations with large mutation supplies adapt via the "greedy" substitution of the fittest genotype available, leading to fast and repeatable short-term responses. At longer time scales, smaller mutation supplies may in theory lead to larger improvements when distant high-fitness genotypes more readily evolve from lower-fitness intermediates. Here we test for long-term adaptive benefits from s...

The present study is an attempt to propose a mutation-based real-coded genetic algorithm (MBRCGA) for sizing and layout optimization of planar and spatial truss structures. The Gaussian mutation operator is used to create the reproduction operators. An adaptive tournament selection mechanism in combination with adaptive Gaussian mutation operators are proposed to achieve an effective search in ...

Aspects of the molecular mechanism of "adaptive" mutation are emerging from one experimental system: reversion of an Escherichia coli lac frameshift mutation carried on a conjugative plasmid. Homologous recombination is required and the mutations resemble polymerase errors. Reports implicating a role for conjugal transfer proteins suggested that the mutation mechanism is ordinary replication er...

An important goal of evolutionary biology is to understand the constraints that shape the dynamics and outcomes of evolution. Here, we address the extent to which the structure of the standard genetic code constrains evolution by analyzing adaptive mutations of the antibiotic resistance gene TEM-1 β-lactamase and the fitness distribution of codon substitutions in two influenza hemagglutinin inh...

Previous studies of Genetic Algorithm (GA) optimization in nonstationary environments focus on discontinuous, Markovian switching environments. This study introduces the problem of GA optimization in continuous, nonstationary environments where the state of the environment is a function of time. The objective of the GA in such an environment is to select a sequence of values over time that mini...

Key words-Genetic Algorithm; Adaptive Genetic Algorithm; crossover probability; mutation probability; image segmentation

Aiming at the coupling of energy consumption and completion time in flexible job-shop scheduling, this paper took makespan as optimization objectives, established a scheduling model, proposed strategy based on improved genetic algorithm. Firstly, hybrid initialization method global minimum selection workload is introduced to generate initial population, scale population expanded increase divers...