Constrained clustering and parallel genetic algorithm on a multiprocessor system FIN

Genetic algorithms (GA) are typically regarded as the unconstrained search procedure within the given representation space. But many actual problems hold one or more constraints that must be satisfied. In this paper, we consider the incorporation of constraints into fitness function and solve the constrained clustering problem using the GA through a multiprocessor system (FIN) which has a self-similarity network.<
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