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This paper presents a segregative genetic algorithm for "I"/U"-shaped assembly line balancing problem. It uses a basic genetic algorithm and a feature function that associates a time profile of the workstations to each chromosome. The similarity based clustering in the feature space induces subpopulations of chromosomes. The segregative genetic algorithm acts both on representation...
This paper presents the design of an accurate fuzzy dependency approximator that uses fuzzy inputs, fuzzy targets and fuzzy weights. The proposed design can cope with arbitrarily discrete membership functions. It is a combination between a Kohonen network used for clustering the fuzzy data and a set of low degree rational fuzzy approximators. The self-organizing system works in fuzzy arithmetic and...
This paper deals with the finding of a fuzzy rational function that best fits on a given set of input-output patterns of an unknown fuzzy dependency. In order to solve this problem a distributed genetic algorithm based on the island model is presented. Experimental investigations for evaluating the performance of the proposed distributed algorithm are also described.
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