Partitioning Sets with Genetic Algorithm

William A. Greene, University of New Orleans, USA

We first revisit a problem in the literature of genetic algorithms: arranging numbers into groups whose summed weights are as nearly equal as possible. We provide a new genetic algorithm which very aggressively breeds new individuals which should be improved groupings of the numbers. Our results improve upon those in the literature. Then we extend and generalize our algorithm to a related class of problems, namely, partitioning a set in the presence of a fitness function that assesses the goodness of subsets participating in the partition. Experimental results of this second algorithm show that it, too, works very well.


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