L. Graham and F. Oppacher (Canada)
Genetic Algorithms, Sorting Networks, Test Case Quality Measures
Sorting networks have been of interest to the computer science and evolutionary computing communities for several decades. In this paper we present a measure of test case quality that may have application to other problems in which fitness is based on a large number of test cases. We use this measure to reduce the number of tests used in fitness evaluation as a means of optimizing the speed of a genetic algorithm, although the quality measure itself is expensive. We report the results of several genetic algorithm experiments evolving sorting networks using a restricted number of test cases, and compare those results to similar experiments in the literature.
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