Crossover Operation of Random Drift Particle Swarm Optimization

Min Yan, Jun Sun, Qidong Chen
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Abstract

In order to enhance the global search capability, a crossover operation based on RDPSO algorithm(CO-RDPSO) is put forward. Through crossover operation, particles can skip the local optimum and strengthen the global search capability. Test CO-RDPSO with twelve functions, the experiment results directions, CO-RDPSO not only obtains better results but also converge faster than other algorithms both on unimodal or multimodal.
随机漂移粒子群优化的交叉运算
为了提高全局搜索能力,提出了一种基于RDPSO算法的交叉运算(CO-RDPSO)。通过交叉运算,粒子可以跳过局部最优,增强全局搜索能力。用12个函数对CO-RDPSO进行了测试,实验结果表明,无论在单峰还是多峰情况下,CO-RDPSO不仅得到了更好的结果,而且收敛速度快于其他算法。
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