A fuzzy logic controlled genetic algorithm environment

This paper proposes a fuzzy logic controlled genetic algorithm (FLC-GA) for the application of star pattern recognition. The proposed FLC-GA dynamically performs operator selection and parameter adjustment automatically. The fuzzy logic controller facilitates this automated control by employing an associated rulebase and inference engine. The rulebase/inference engine decides, using feedback from the genetic algorithm, what control action to take and when to take it. Results from our experiments indicate that optimal solutions evolve more rapidly, thus reducing the time taken to locate a solution within the search space