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This paper deals with a novel buffer management scheme based on the combination of evolutionary computing and fuzzy logic for shared-memory packet switches. The philosophy behind it is adaptation of the threshold for each logical output queue to the real traffic conditions by means of a system of fuzzy inferences. The optimal fuzzy system is achieved using a systematic methodology based on Genetic Algorithms for membership-function selecting and tuning. This methodology approach allows the fuzzy system parameters to be automatically derived when the switch parameters vary, offering a high degree of scalability to the fuzzy control system. Its performance is close to that of the push-out mechanism, which can be considered ideal from a performance viewpoint, and at any rate much better than that of threshold schemes based on conventional logic. In addition, the fuzzy threshold scheme is simple to implement, unlike the push-out mechanism which is not practically feasible in high-speed switches due to the amount of time required for computation, and above all inexpensive when implemented using current standard technology.