Genetical and Evolutional Algorithms

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Department of Applied Informatics in Transportation

Synopsis:

Optimization, problem classes (P, NP, NP-complete)

Darwins, Baldwin's and Lamarck's evolutionary theories, evolutional technique principles

Genetic algorithms

Fitness function and its modifications

Selection principles

Evolution strategy

Differential evolution

Grammatical evolution

Genetic programming

GPA

SOMA

Applications of evolutional techniques

Simulated annealing

GP and GA in machinery learning

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The course is a part of the following study plans: