Course notes: genetic algorithm theory
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- Course notes: genetic algorithm theory
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Theory of the simple genetic algorithm with α-selection, uniform crossover and bitwise mutation
Genetic algorithms (GA) are instances of random heuristic search (RHS) which mimic biological evolution and molecular genetics in simplified form. These random heuristic search algorithms can be theoretically described by an infinite population model ...
The intrinsic system model of the simple genetic algorithm with α-selection, uniform crossover and bitwise mutation
ICS'10: Proceedings of the 14th WSEAS international conference on Systems: part of the 14th WSEAS CSCC multiconference - Volume IIGenetic algorithms (GA) are instances of random heuristic search (RHS) which mimic biological evolution and molecular genetics in simplified form. These random search algorithms can be theoretically described with the help of a deterministic dynamical ...
An improved genetic algorithm with conditional genetic operators and its application to set-covering problem
The genetic algorithm (GA) is a popular, biologically inspired optimization method. However, in the GA there is no rule of thumb to design the GA operators and select GA parameters. Instead, trial-and-error has to be applied. In this paper we present an ...
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