2 research outputs found

    Genetic Algorithm with Modified Crossover for Grillage Optimization

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    Modified genetic algorithm with special phenotypes' selection and crossover operators with default specified rules is proposed in this paper thus refusing the random crossover. The suggested crossover operator enables wide distribution of genes of the best phenotypes over the whole population. During selection and crossover, the best phenotypes of the newest population and additionally the genes of the best individuals of two previous populations are involved. The effectiveness of the modified algorithm is shown numerically on the real-life global optimization problem from civil engineering - the optimal pile placement problem under grillage-type foundations. This problem is a fair indicator for global optimization algorithms since the ideal solutions are known in advance but with unknown magnitudes of design parameters. Comparison of the proposed algorithm with 6 other stochastic optimization algorithms clearly reveals its advantages: at similar accuracy level the algorithm requires less time for tuning of genetic parameters and provides narrower confidence intervals on the results than other algorithms

    Metai ir dienos. VGTU 2013 m.

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    Leidinyje aprašomi VGTU 2013 metų pagrindiniai įvykiai, mokslo ir studijų plėtotė, tarptautinis bendradarbiavimas, dalyvavimas tarptautinėse konferencijose, senato ir rektorato priimti sprendimai ir kt. Taip pat pateikiama žinių apie universiteto padalinius: fakultetus, katedras, centrus, institutus ir kt. Leidinys skirtas plačiajai visuomenei
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