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An improved GA and a novel PSO-GA-based hybrid algorithm

机译:改进的遗传算法和基于PSO-GA的新型混合算法

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摘要

Inspired by the natural features of the variable size of the population, we present a variable population-size genetic algorithm (VPGA) by introducing the "dying probability" for the individuals and the "war/disease process" for the population. Based on the VPGA and the particle swarm optimization (PSO) algorithms, a novel PSO-GA-based hybrid algorithm (PGHA) is also proposed in this paper. Simulation results show that both VPGA and PGHA are effective for the optimization problems.
机译:受人口规模可变的自然特征的启发,我们通过引入个体的“死亡概率”和人口的“战争/疾病过程”,提出了人口规模可变的遗传算法(VPGA)。基于VPGA和粒子群优化算法,提出了一种基于PSO-GA的混合算法PGHA。仿真结果表明,VPGA和PGHA均可有效解决优化问题。

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