Novel Knowledge Based Tabu Crossover In Genetic Algorithms
نویسنده
چکیده
Genetic algorithms are optimisation algorithms and mimic the natural process of evolution. Important operators used in genetic algorithms are selection, crossover and mutation. Selection operator is used to select the individuals from a population to create a mating pool which will participate in reproduction process. Crossover and mutation operators are used to introduce diversity in the population. This paper studies different crossover operators and then proposes a novel crossover operator that incorporates knowledge based on existing population and uses the principle of Tabu search. Performance of the proposed tabu crossover is compared with existing PMX operator in genetic algorithm using MATLAB code. Keywords— crossover, genetic algorithm, hybridisation, memetic algorithm, tabu list,
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