LIU Liqin,SUN Bo,WANG Baoyun,et al.Research on a quantum particle swarm optimization algorithmbased on differential evolution[J].Journal of Yanbian University,2019,45(02):141-144.
基于差分进化的量子粒子群优化算法的研究
- Title:
- Research on a quantum particle swarm optimization algorithm based on differential evolution
- 文章编号:
- 1004-4353(2019)02-0141-04
- 分类号:
- TP18; TN929
- 文献标志码:
- A
- 摘要:
- 为了提高量子粒子群算法(QPSO)的性能,利用差分进化对量子粒子群算法进行了优化.该优化算法(DE -QPSO)在粒子更新过程中,首先通过添加一个扰动来产生一个变异粒子,然后对变异粒子进行交叉操作产生新的试验粒子,最后对试验粒子进行选择操作,确定进入下一次迭代的个体.用5种标准测试函数对DE -QPSO、QPSO和 粒子群算法(PSO)的性能进行对比测试,结果表明DE-QPSO算法的性能明显优于PSO和QPSO算法,具有较好的应用价值.
- Abstract:
- In order to improve the performance of QPSO, differential evolution is used to optimize QPSO. Firstly, a disturbance is added to generate a mutant particle, and then the mutant particles are cross-operated to generate new experimental particles, and finally the test particles are selected to select the individual for the next iteration. The performance of the optimized algorithm(DE-QPSO), PSO and QPSO proposed in this paper is compared and tested with five kinds of standard test functions. The results show that the performance of DE-QPSO is obviously better than that of PSO and QPSO, and has good application value.
参考文献/References:
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备注/Memo
收稿日期: 2019-04-20 作者简介: 留黎钦(1982—),女,讲师,研究方向为智能信号处理.
*基金项目: 国家自然科学基金资助项目(61702103); 福建省自然科学基金资助项目(2016J01289)