[1]李岩,张光武. 混合NSGAII和DE的优化算法及应用[J].哈尔滨理工大学学报,2018,(05):75-79.[doi:10.15938/j.jhust.2018.05.013]
 LI Yan,ZHANG Guang wu.Optimization Algorithm and Application of Hybrid NSGAII and DE[J].哈尔滨理工大学学报,2018,(05):75-79.[doi:10.15938/j.jhust.2018.05.013]
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 混合NSGAII和DE的优化算法及应用()
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《哈尔滨理工大学学报》[ISSN:1007-2683/CN:23-1404/N]

卷:
期数:
2018年05期
页码:
75-79
栏目:
计算机与控制工程
出版日期:
2018-10-25

文章信息/Info

Title:
Optimization Algorithm and Application of Hybrid NSGAII and DE
作者:
 李岩张光武
(哈尔滨理工大学 计算机科学与技术学院,黑龙江 哈尔滨 150080)
Author(s):
 LI YanZHANG Guangwu
 (School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China)
关键词:
 关键词:遗传算法NSGAII差分进化算法MATLAB软硬件划分
Keywords:
 Keywords:genetic algorithm NSGAII differential evolution algorithm MATLAB softwarehardware partitioning
分类号:
TP3162
DOI:
10.15938/j.jhust.2018.05.013
文献标志码:
A
摘要:
 摘要:遗传算法NSGAII在引入快速非支配排序算法、拥挤度算子以及精英策略后重复个体产生的概率明显上升,降低了帕累托效率。针对这一缺陷进行了改进,去除了重复个体并保持种群数量不变。根据遗传算法基因交叉变异的方法和差分进化算法DE的思想,将改进后的NSGAII算法与DE算法进行有效混合构建一种新的多目标优化算法。通过MATLAB对优化后的算法进行验证,结果表明优化后的算法在分布性和收敛性上都有所提高,搜索解的能力也有所提升。然后利用优化后的算法完成对μC/OSII任务管理部分的软硬件划分。
Abstract:
 Abstract:Due to the introduction of fast nondominated sorting algorithms, crowding operators and elite strategy, the probability of repetition individual increased significantly in every population of NSGAII algorithm, reducing the Pareto efficiency It has been improved for this defect, removed the repeating individual and maintained the number of populations unchanged According to the genetic algorithm crossover and mutation method and differential evolution algorithm DE, the improved NSGAII and DE are combined to construct a new multiobjective optimization algorithm The algorithm takes DE as the main optimization method, and uses the basic idea and crossover and mutation method of genetic algorithm The optimization algorithm was verified by MATLAB The results show that the optimized algorithm has been improved in both distribution and convergence, and the capacity of search solution has also been improved At last , the optimization algorithm is used to complete the hardwaresoftware partitioning of task management part in μC/OSII

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备注/Memo

备注/Memo:
 基金项目:哈尔滨市优秀学科带头人基金(2013RFXXJ034);黑龙江省自然科学基金(F2015038)
更新日期/Last Update: 2018-11-14