In the context of systems and cybernetics theory, we present a new general stochastic method of search and optimization of solutions of problems that we have named Prototyped Genetic Search. Our new method is based mainly on prototype and learning concepts, although it uses concepts of population and evolution just as Evolutionary Algorithms. Moreover, and in order to show the interest of this method and to demonstrate its real potential, we have chosen to apply it on the Job‐Shop Scheduling Problem in the context of the flexible production. This paper is also the opportunity for us to present an other new kind of genetic algorithms, resulting from the integration of the recursivity in the basis functioning of genetic algorithms, and that we have named Recursive Genetic Algorithm.
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