An introduction to genetic algorithms
An introduction to genetic algorithms
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Adapting Operator Probabilities in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Genetic algorithms and artificial life
Artificial Life
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The aim of this paper is to study two new forms of genetic operators: duplication and fabrication. Duplication is a reproduce procedure that will reproduce the best fit chromosome from the elite base. The introduction of duplication operator into the modified GA will speed up the convergence rate of the algorithm however the trap into local optimality can be avoided. Fabrication is an artificial procedure used to produce one or several chromosomes by mining gene structures from the elite chromosome base. Statistical inference by job assignment procedure will be applied to produce artificial chromosomes and these artificial chromosomes provides new search directions and new solution spaces for the modified GA to explore. As a result, better solution quality can be achieved when applying this modified GA. Different set of problems will be tested using modified GA by including these two new operators in the procedure. Experimental results show that the new operators are very informative in searching the state space for higher quality of solutions.