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Greene, William A. - Department of Computer Science, University of New Orleans
GENETIC ALGORITHMS FOR PARTITIONING SETS WILLIAM A. GREENE
We first revisit a problem in the literature of genetic algo-rithms: arranging numbers into groups whose summed
We produce a GA scheduling routine, which with often relatively low cost finds well-balanced schedules.
Abstract: We present a clustering algorithm which is unsupervised, incremental, and hierarchical. The algo-
We present a novel representation and crossover operator for genetic algorithms. Bits are not
We generalize Holland's Schema Theorem to the setting that genes are arranged, not necessarily in
In earlier research we laid out a theoretical basis for the supposition that genetic algorithms can
Abstract: We present a local improvement heuristic for genetic algorithms, and term it a Kernighan-Lin
Schema Disruption in Tree-Structured Chromosomes William A. Greene
Schema Disruption in Chromosomes that are Structured as Binary Trees
Our earlier research laid a theoretical basis for the contention that genetic algorithms can succeed
ECONOMICAL TRAINING SETS FOR LINEAR ID3 LEARNING William A. Greene, Ph.D.
Abstract: We present a divide-and-conquer algo-rithm for merging k sorted lists, namely, recur-
Abstract: The machine learning algorithm of [3] is ap-plied to the problem of learning which heuristics to apply
Technical Report A primer on Bethke's Walsh schema transform
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