Abstract
In this paper the relative performance of two constraint handling techniques, namely a parameter-less adaptive penalty method (APM) and the stochastic ranking method (SR), is studied in the context of continuous parameter constrained optimization problems. Both techniques are used within the same search engine, a binary-coded genetic algorithm.
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