Using Time Efficiently: Genetic-Evolutionary Algorithms and the Continuation Problem

This paper develops a macro-level theory of efficient time utilization for genetic and evolutionary algorithms. Building on population sizing results that estimate the critical relationship between solution quality and time, the paper considers the tradeoff between large populations that converge in a single convergence epoch and smaller populations with multiple epochs. Two models suggest a link between the salience structure of a problem and the appropriate population-time configuration for best efficiency.

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