Imitation of bee reproduction as a crossover operator in genetic algorithms - Karci, A (Springer-Verlag Berlin, 2004)
There are lots of methods inpired by the natural observations (i.e. fuzzy logic, artificial neural networks, genetic algorithms, simulated annealing algorithms, etc.) This paper proposes a novel crossover operator type inspired by the sexual intercourses of honey bees. The method selects a specific chromosome in present population as queen bee. While the selected queen bee is one parent of crossover, all the remaining chromosomes have the chance to be next parent for crossover in each generation once. For this purposes, we defined three honey bee crossover methods: In the first method, the chromosome with the best fitness score is queen honey bee and it is a fixed parent for crossover in the current generation. The second method handles the chromosome with the worst fitness score. Finally, queen bee is changed sequentially in each generation.
8th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2004) -- AUG 09-13, 2004 -- Auckland, NEW ZEALAND