An Improved Immune Genetic Algorithm for Solving the Optimization Problems of Computer Communication

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Obtaining the average delay and selecting a route in a communication network are multi-constrained nonlinear optimization problems. In this paper, based on the immune genetic algorithm, a new fuzzy self-adaptive mutation operator and a new upside-down code operator are proposed. This improved IGA is further successfully applied to solve optimal problems of computer communication nets.
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