The method includes: converting a solution set space formed by a decision variable into a population; initializing the population and algorithm parameters of the population; generating a donation vector, a trial vector, and a subgeneration according to the algorithm parameters of the population; adding the subgeneration into the population to obtain a mutational population , and decoding an individual to obtain adaptability; determining whether a current quantity of iterations i is less than a total quantity of iterations; if so, selecting an individual in the mutational population, generating a new population, and updating algorithm parameters of a corresponding population; otherwise, removing a dominated solution in an elite solution set, and adding a non-dominated solution in the mutational population into solutions that are not dominated by an individual in the elite solution set, so as to update the elite solution set; and step 8: sorting individuals in the elite solution set, and outputting a specified quantity of individuals according to an obtained sorting sequence.
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