Displaying similar documents to “An evolutionary approach to geometrical place problems.”

Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Angelova, Maria, Tzonkov, Stoyan, Pencheva, Tania (2010)

Serdica Journal of Computing

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Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for...

The impatience mechanism as a diversity maintaining and saddle crossing strategy

Iwona Karcz-Duleba (2016)

International Journal of Applied Mathematics and Computer Science

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The impatience mechanism diversifies the population and facilitates escaping from a local optima trap by modifying fitness values of poorly adapted individuals. In this paper, two versions of the impatience mechanism coupled with a phenotypic model of evolution are studied. A population subordinated to a basic version of the impatience mechanism polarizes itself and evolves as a dipole centered around an averaged individual. In the modified version, the impatience mechanism is supplied...

Time to the convergence of evolution in the space of population states

Iwona Karcz-Dulęba (2004)

International Journal of Applied Mathematics and Computer Science

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Phenotypic evolution of two-element populations with proportional selection and normally distributed mutation is considered. Trajectories of the expected location of the population in the space of population states are investigated. The expected location of the population generates a discrete dynamical system. The study of its fixed points, their stability and time to convergence is presented. Fixed points are located in the vicinity of optima and saddles. For large values of the standard...

Theoretical analysis of steady state genetic algorithms

Alexandru Agapie, Alden H. Wright (2014)

Applications of Mathematics

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Evolutionary Algorithms, also known as Genetic Algorithms in a former terminology, are probabilistic algorithms for optimization, which mimic operators from natural selection and genetics. The paper analyses the convergence of the heuristic associated to a special type of Genetic Algorithm, namely the Steady State Genetic Algorithm (SSGA), considered as a discrete-time dynamical system non-generational model. Inspired by the Markov chain results in finite Evolutionary Algorithms, conditions...