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改进多元宇宙算法求解大规模实值优化问题

本站小编 Free考研考试/2022-01-03

刘小龙,
华南理工大学工商管理学院 广州 510641
基金项目:国家自然科学基金(71471065, 71571072, 71771091),广州社科联基金(2018GZGJ02)

详细信息
作者简介:刘小龙:男,1977年生,讲师,研究方向为仿生优化与计算智能
通讯作者:刘小龙 xlliu@scut.edu.cn
中图分类号:TP301.6

计量

文章访问数:2025
HTML全文浏览量:803
PDF下载量:68
被引次数:0
出版历程

收稿日期:2018-07-22
修回日期:2019-01-17
网络出版日期:2019-02-14
刊出日期:2019-07-01

Application of Improved Multiverse Algorithm to Large Scale Optimization Problems

Xiaolong LIU,
School of Business Administration, South China University of Technology, Guangzhou 510641, China
Funds:The National Natural Science Foundation of China (71471065, 71571072, 71771091), Guangzhou Social Science Federation Fund (2018GZGJ02)


摘要
摘要:针对多元宇宙优化(MVO)算法中虫洞存在机制、白洞选择机制等不足,该文提出一种改进多元宇宙优化算法(IMVO)。设计固定概率的虫洞存在机制和前期快速收敛后期平缓收敛的虫洞旅行距离率,加快算法全局探索能力和快速迭代能力;提出黑洞的随机白洞选择机制,设计黑洞围绕白洞恒星进行公转并模型化,解决代间宇宙信息沟通的问题,中低维度数值比较实验验证了改进算法的优良性能。选取大规模实值问题较难优化的3个基准测试函数进行对比实验,改进算法在大规模优化问题上的求解精度和成功率方面具有较好的适用性和鲁棒性。
关键词:大规模优化问题/
多元宇宙优化/
元启发式优化/
非线性收敛因子
Abstract:To overcome the mechanism shortcomings of wormhole and white hole selection in the Multi-Verse Optimizer (MVO), an Improved Multi-Universes Optimization (IMVO) algorithm is proposed. To speed up global exploration ability and quick iteration ability, this thesis designs the existence mechanism of wormhole with fixed probability and the Travel Distance Rate (TDR) that its convergence from early stage's smoothly to later stage's fast. The random white hole selection mechanism is proposed; Black holes can revolve around selected white hole stars and is modelled to solve the problem of information communication of the Inter-generational Universes. The performance of IMVO is verified by comparison experiments in low-middle dimensions. Three benchmarks test functions are selected for comparison in large scale which are difficult to be optimized, the experimental results show that IMVO has good applicability and robustness with higher solving accuracy and success rate in large scale optimization problem.
Key words:Large scale optimization problem/
Multi-Verses Optimization (MVO)/
Meta heuristic optimization/
Non-linear convergence factor



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