Genetic fuzzy logic controllers add more complexity to the fuzzy production control space but the designer can be sure that the obtained fuzzy controller is the optimized one furthermore the process of designing membership function in fuzzy production control which is a time consuming and non precise process can be ignored by implementing gas . Genetic fuzzy systems are fuzzy systems constructed by using genetic algorithms or genetic programming which mimic the process of natural evolution to identify its structure and parameter when it comes to automatically identifying and building a fuzzy system given the high degree of nonlinearity of the output traditional linear optimization tools have several limitations. Improvement in the performance of production control systems is so important that many of past studies were dedicated to this problem the applicability of fuzzy controllers in production control . A fuzzy control system is a control system based on fuzzy logic a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1 in contrast to classical or digital logic which operates on discrete values of either 1 or 0 true or false respectively. North hoiiand tuning fuzzy logic controllers by genetic algorithms f herrera m lozano and j l verdegay department of computer science and artificial intelligence university of granada spain abstract the performance of a fuzzy logic controller depends on its control rules and membership functions
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