An introduction to genetic algorithms
An introduction to genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Parallel Substitution Algorithm: Theory and Application
Parallel Substitution Algorithm: Theory and Application
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A universal approach for describing the population model of genetic algorithms is developed which is based on the Parallel Substitution Algorithm (PSA) theory. Genetic algorithms (GA) are a suitable method if good approximations for problems are required which were otherwise not solvable in practical environments. Optimisation of GAs can be done on several levels, in this work we concentrate on the population model. Most prominent population models are the classical global model, the island model and it's extreme variant, the cellular model. The PSA theory supports us with a general approach which is essential for systematically studying convergence behaviour of GA population model variants and consequently for their optimisation.