检索结果-内蒙古大学图书馆

A hybrid niching PSO enhanced with recombination-replacement crowding strategy for multimodal function optimization

APPLIED SOFT COMPUTING 2012年第3期12卷 975-987页

作者： Li, Minqiang Lin, Dan Kou, Jisong Tianjin Univ Sch Management Tianjin 300072 Peoples R China

This paper presents a hybrid niching algorithm based on the PSO to deal with multimodal function optimization problems. First, we propose to evolve directly both the particle population and memory population (archive population), called the P&A pattern, to enhance the efficiency of the PSO for solving multimodal optimization functions, and investigate illustratively the niching capability of the PSO and the PSOP&A. It is found that the global version PSO is disable, but the local version PSOP&A is able, to niche multiple species for locating multiple optima. Second, the recombination-replacement crowding strategy that works on the archive population is introduced to improve the exploration capability, and the hybrid niching PSOP&A (HN-PSOP&A) is developed. Finally, experiments are carried out on multimodal functions for testing the niching efficiency and scalability of the proposed method, and it is verified that the proposed method has a sub-quadratic scalability with dimension in terms of fitness function evaluations on specific MMFO problems. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Particle swarm optimization Niching Recombination-replacement crowding multimodal function optimization

来源：评论

学校读者我要写书评

暂无评论

A REVIEW OF NICHING GENETIC ALGORITHMS FOR multimodal function optimization

引用

CYBERNETICS AND SYSTEMS ANALYSIS 2013年第6期49卷 815-820页

作者： Glibovets, N. N. Gulayeva, N. M. Natl Univ Kyiv Mohyla Acad Kiev Ukraine

In this paper, a comprehensive review of approaches to solve multimodal function optimization problems via genetic niching algorithms is provided. These algorithms are presented according to their space-time classification. Methods based on fitness sharing and crowding methods are described in detail as they are the most frequently used.

关键词： genetic algorithm multimodal function optimization niching methods

来源：评论

学校读者我要写书评

暂无评论

Efficient differential evolution using speciation for multimodal function optimization 05

Efficient differential evolution using speciation for multim...

引用

Genetic and Evolutionary Computation Conference

作者： Li, Xiaodong RMIT Univ Sch Comp Sci & IT Melbourne Vic Australia

ISBN: (纸本)1595930108

In this paper differential evolution is extended by using the notion of speciation for solving multimodal optimization problems. The proposed species-based DE (SDE) is able to locate multiple global optima simultaneously through adaptive formation of multiple species (or subpopulations) in an DE population at each iteration step. Each species functions as an DE by itself. Successive local improvements through species formation can eventually transform into global improvements in identifying multiple global optima. In this study the performance of SDE is compared with another recently proposed DE variant CrowdingDE. The computational complexity of SDE, the effect of population size and species radius on SDE are investigated. SDE is found to be more computationally efficient than CrowdingDE over a number of benchmark multimodal test functions.

关键词： algorithms evolutionary computation differential evolution multimodal function optimization

来源：评论

学校读者我要写书评

暂无评论

A new algorithm based on immune algorithm and Hopfield neural network for multimodal function optimization

A new algorithm based on immune algorithm and Hopfield neura...

引用

6th International Conference on Machine Learning and Cybernetics

作者： Li, Na-Na Dong, Yong-Feng Gu, Jun-Hua Zhou, Rui-Ying Tianjin Univ Sch Comp Sci & Technol Tianjin 300072 Peoples R China Hebei Univ Technol Sch Comp Sci & Engn Tianjin Peoples R China

ISBN: (纸本)9781424409723

This paper analyzes immune theory and Hopfield Neural Network (HNN), and then proposes a new algorithm for multimodal function. This new algorithm uses the advantages of both HNN and immune algorithm, and it appears excellent characteristic in optimal problems of multimodal function. In detail, we obtain a group of solutions with variety by immune algorithm (IA) first;and then the solutions are partitioned into some clusters. Finally we take cluster centroids returned by clustering algorithm as the initial value of each HNN, and run the Hopfield neural networks to obtain all minima.

关键词： Hopfield network immune algorithm cluster multimodal function optimization

来源：评论

学校读者我要写书评

暂无评论

Research of Community Discovery Algorithm Guided by multimodal function optimization

Research of Community Discovery Algorithm Guided by Multimod...

引用

International Symposium on Information and Automation (ISIA 2010)

作者： Ma Rui-xin Wang Xiao Dalian Univ Technol Software Sch Dalian 116022 Peoples R China

ISBN: (纸本)9783642198526

This paper introduces the concept of community seed, comes up with a novel algorithm which based on the multimodal function optimization idea. Generally, the relationship between\\nodes in the same community is much closer than nodes in different communities. We use different sizes of network structures Zachary and Dolphins to test our algorithm, the experimental results show that this method is able to finish dividing the network in low time complexity, high efficiency without any priori information.

关键词： Community discovery priori information community seed multimodal function optimization

来源：评论

学校读者我要写书评

暂无评论

Immune Multi-population Firefly Algorithm and Its Application in multimodal function optimization 9

Immune Multi-population Firefly Algorithm and Its Applicatio...

引用

9th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Zhou, Jiufang Wu, Jianhui Chen, Hua Hunan Univ Coll Comp Sci & Elect Engn Changsha Hunan Peoples R China

ISBN: (纸本)9781538665657

In this paper, a novel immune multl-populanon firefly algorithm (IMPFA) is presented to solve multimodal function optlmlzatton problems. The proposed algorithm integrates multi population firefly algorithm (MPFA) with non-uniform mutation clonal selection algorithm (NUMCSA). In each loop iteration, firstly, the MPFA based on multl-populatten learnmg mechanism is used to search globally in the feasible region, and then the NUM CSA is utilized to search locally for improving the accuracy of the sub-optlmal solutions obtained with MPFA. Simulation results show that the IMPFA is extremely effective and increases the precision of solutions.

关键词： immune multi-population fir efl) algorithm multimodal function optimization clonal selection algorithm

来源：评论

学校读者我要写书评

暂无评论

A steepest descent evolution immune algorithm for multimodal function optimization

引用

2nd International Symposium on Intelligence Computation and Application (ISICA 2007)

作者： Zhu, Li Li, Zhishu Sun, Bin Sichuan Univ Sch Comp Chengdu Peoples R China Chengdu Sport Univ Network Ctr Chengdu Peoples R China Chengdu Aircraft Corp Ctr Dev & Engn Chengdu Peoples R China

ISBN: (纸本)9783540745808

This paper presents an novel evolution and immune hybrid algorithm for multimodal function optimization. The algorithm constructs a multidimensional shape-space based on immune theory and approaches optima by steepest descent evolution strategy along each dimension, adjusts steps adaptively based on fitness in each iteration, as a result, gets steepest and surefooted ability approaching the optima. By suppressing close individuals in immune shape-space within a restraint radius and supplying new individuals to exploit new searching space, the algorithm obtains very good diversity. Experiments for multimodal functions show that the algorithm achieved global searching effect, obtained all the optima in shorter iterations and with lesser size of population compared with the GA, CSA and op-aiNet.

关键词： immune evolution strategy steepest descent multimodal function optimization

来源：评论

学校读者我要写书评

暂无评论

Niche Differential Evolution Algorithm and Its Application in multimodal function optimization

Niche Differential Evolution Algorithm and Its Application i...

引用

International Conference on Advanced Design and Manufacturing Engineering (ADME 2011)

作者： Li, Na Li, Yuanxiang Huang, Zhiguo Wang, Yong Wuhan Univ State Key Lab Software Engn Wuhan 430072 Peoples R China

ISBN: (纸本)9783037852132

In multimodal optimization, the original differential evolution algorithm is easy to duplicate and miss points of the optimal value. To solve this problem, a modified differential evolution algorithm, called niche differential evolution (NDE), is proposed. In the algorithm, the basic differential evolution algorithm is improved based on the niche technology. The rationality to construct the proposed algorithm is discussed. Shubert function, a representative multimodal optimization problem is used to verify the algorithm. The results show that the proposed algorithm can find all global optimum points quickly without strict request for parameters, so it is a good approach to find all global optimum points for multimodal functions.

关键词： multimodal function optimization differential evolution niche technology

来源：评论

学校读者我要写书评

暂无评论

Study on chaos immune network algorithm for multimodal function optimization

Study on chaos immune network algorithm for multimodal funct...

引用

4th International Conference on Fuzzy Systems and Knowledge Discovery

作者： Jia, L., V Chongqing Normal Univ Coll Math & Comp Sci Chongqing Peoples R China

multimodal function optimization problem, which requires finding out the global optimum and the utmost number of local optima, has important applications in the field of engineering. When solving multimodal function optimization problem with artificial immune network algorithm, problems such as premature convergence phenomena and unsatisfying searching precision may arise. Under such circumstances, improved chaos immune network algorithm was put forward in this paper. In the improved algorithm, the stopping criterion was improved and some relevant measures taken to avoid premature convergence;and chaos variable was used to simulate proliferation mode of immune cells to enhance searching precision. Based on simulation tests on some benchmark functions, conclusions were drawn that this algorithm can fast optimize the antibodies, strengthen the searching ability and enhance the searching precision.

关键词： multimodal function optimization artificial immune network algorithm chaos immune network algorithm

来源：评论

学校读者我要写书评

暂无评论

A Simple and Effective Evolutionary Algorithm for multimodal function optimization

A Simple and Effective Evolutionary Algorithm for Multimodal...

引用

智能计算及其应用国际会议

作者： JIANG Dazhi1, WU Zhijian1 , KANG Lishan1, 2 (1. State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China) (2. Department of Computer Science and Technology, China University of Geosciences, Wuhan 430074, China)

It is hard for conventional method to find all the global optimal solutions at one time for the multimodal function optimization problems. Although sometimes all the global optimal solutions can be ac

关键词： evolutionary computation self-adaptive niche selection technology cellular automata multimodal function optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：