检索结果-南通市图书馆

Zoning Search With Adaptive Resource Allocating Method for Balanced and Imbalanced multimodal multi-objective optimization

引用

IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1163-1176页

作者： Qinqin Fan Okan K.Ersoy Logistics Research Center Shanghai Maritime UniversityShanghai 201306China School of Electronic and Computer Engineering Purdue UniversityWest LafayetteIN 47906 USA

Maintaining population diversity is an important task in the multimodal multi-objective *** the zoning search(ZS)can improve the diversity in the decision space,assigning the same computational costs to each search subspace may be wasteful when computational resources are limited,especially on imbalanced *** alleviate the above-mentioned issue,a zoning search with adaptive resource allocating(ZS-ARA)method is proposed in the current *** the proposed ZS-ARA,the entire search space is divided into many subspaces to preserve the diversity in the decision space and to reduce the problem ***,the computational resources can be automatically allocated among all the *** ZS-ARA is compared with seven algorithms on two different types of multimodal multi-objective problems(MMOPs),namely,balanced and imbalanced *** results indicate that,similarly to the ZS,the ZS-ARA achieves high performance with the balanced ***,it can greatly assist a“regular”algorithm in improving its performance on the imbalanced MMOPs,and is capable of allocating the limited computational resources dynamically.

关键词： Computational resource allocation decision space decomposition evolutionary computation multimodal multi-objective optimization

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Hybrid Operator and Strengthened Diversity Improving for multimodal multi-objective optimization

引用

Tsinghua Science and Technology 2024年第5期29卷 1409-1421页

作者： Guoting Zhang Yonghao Du Xiaobin Zhu Xiaolu Liu Beijing Institute of Tracking and Telecommunication Technology Beijing 100094China College of Systems Engineering National University of Defense TechnologyChangsha 410073China

multimodal multi-objective optimization problems(MMOPs)contain multiple equivalent Pareto subsets(PSs)corresponding to a single Pareto front(PF),resulting in difficulty in maintaining promising diversities in both objective and decision spaces to find these *** used to solve MMOPs,evolutionary algorithms mainly consist of evolutionary operators that generate new solutions and fitness evaluations of the *** enhance performance in solving MMOPs,this paper proposes a multimodal multi-objective optimization evolutionary algorithm based on a hybrid operator and strengthened diversity ***,a hybrid operator mechanism is devised to ensure the exploration of the decision space in the early stage and approximation to the optima in the latter ***,an elitist-assisted differential evolution mechanism is designed for the early exploration *** addition,a new fitness function is proposed and used in environmental and mating selections to simultaneously evaluate diversities for PF and *** studies on 11 widely used benchmark instances from a test suite verify the superiority or at least competitiveness of the proposed methods compared to five state-of-the-art algorithms tailored for MMOPs.

关键词： multimodal multi-objective optimization evolutionary algorithm hybrid operator strengthened diversity

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Exploring a Promising Region and Enhancing Decision Space Diversity for multimodal multi-objective optimization

引用

Tsinghua Science and Technology 2024年第2期29卷 325-342页

作者： Fei Ming Wenyin Gong School of Computer Science China University of GeosciencesWuhan 430074China

During the past decade,research efforts have been gradually directed to the widely existing yet less noticed multimodal multi-objective optimization problems(MMOPs)in the multi-objective optimization ***,researchers have begun to investigate enhancing the decision space diversity and preserving valuable dominated solutions to overcome the shortage caused by a preference for objective space ***,many existing methods still have limitations,such as giving unduly high priorities to convergence and insufficient ability to enhance decision space *** overcome these shortcomings,this article aims to explore a promising region(PR)and enhance the decision space diversity for handling *** traditional methods,we propose the use of non-dominated solutions to determine a limited region in the PR in the decision space,where the Pareto sets(PSs)are included,and explore this region to assist in solving ***,we develop a novel neighbor distance measure that is more suitable for the complex geometry of PSs in the decision space than the crowding *** on the above methods,we propose a novel dual-population-based coevolutionary *** studies on three benchmark test suites demonstrates that our proposed methods can achieve promising performance and versatility on different *** effectiveness of the proposed neighbor distance has also been justified through comparisons with crowding distance methods.

关键词： multimodal multi-objective optimization evolutionary algorithms promising region neighbor distance decision space coevolution

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

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：