关键词: 多目标进化算法, 合作型协同进化遗传算法, 外部档案

Abstract: Aiming at the problem of premature convergence and insufficient diversity in traditional multi-objective optimization algorithm, it proposes an improved non-dominated sorting cooperative coevolutionary genetic algorithm. The algorithm uses an external archive storage elite individuals which generate each evolutionary process, and the elitism individuals are updated constantly in the external archive, thus speeding up the convergence rate. Meanwhile, this algorithm improves the diversity of candidate solutions by proposing a new kind of co-evolution between sub-populations. Compared with well-known multi-objective evolutionary algorithm NSGA-II and multi-objective coevolutionary algorithm NSCCGA on a suite of standard ZDT test function, the proposed algorithm has the better convergence and better uniform distribution.