检索结果-内蒙古大学图书馆

4th IEEE International Conference on Cloud Computing and Intelligence Systems (IEEE CCIS)

作者： Xiu, Jiapeng He, Qun Yang, Zhengqiu Liu, Chen Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China

ISBN: (纸本)9781509012565

To overcome the defects of partial multi-objective constrained optimization evolutionary algorithms especially in getting local optimal solutions, poor diversity and robustness, a hybrid algorithm which is named NCCMOEA (Non-dominated Clonal constrained multi-objective optimization Evolutionary Algorithm) is proposed in this paper. This new algorithm combines the Pareto constrained-dominance, improved stochastic ranking algorithm and clone method in immune multi-objective optimization algorithm. Experiments show that compared with the other effective algorithms, this algorithm NCCMOEA is more excellent in diversity and robustness and avoid getting local optimal solutions obviously.

关键词： multi-objective constrained optimization multi-objective constrained optimization Evolutionary Algorithm NCCMOEA

来源：评论

学校读者我要写书评

暂无评论

New Dynamic multi-objective constrained optimization Evolutionary Algorithm

引用

ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2015年第5期32卷 1550036-1550036页

作者： Liu, Chun-An Wang, Yuping Ren, Aihong Baoji Univ Arts & Sci Dept Math Baoji 721013 Shaanxi Peoples R China Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China

For dynamic multi-objective constrained optimization problem (DMCOP), it is important to find a sufficient number of uniformly distributed and representative dynamic Pareto optimal solutions. In this paper, the time period of the DMCOP is first divided into several random subperiods. In each random subperiod, the DMCOP is approximately regarded as a static optimization problem by taking the time subperiod fixed. Then, in order to decrease the amount of computation and improve the effectiveness of the algorithm, the dynamic multi-objective constrained optimization problem is further transformed into a dynamic bi-objective constrained optimization problem based on the dynamic mean rank variance and dynamic mean density variance of the evolution population. The evolution operators and a self-check operator which can automatically checkout the change of time parameter are introduced to solve the optimization problem efficiently. And finally, a dynamic multi-objective constrained optimization evolutionary algorithm is proposed. Also, the convergence analysis for the proposed algorithm is given. The computer simulations are made on four dynamic multi-objective optimization test functions and the results demonstrate that the proposed algorithm can effectively track and find the varying Pareto optimal solutions or the varying Pareto fronts with the change of time.

关键词： Dynamic optimization multi-objective constrained optimization Pareto optimal solution Pareto front time parameter

来源：评论

学校读者我要写书评

暂无评论

Application research in multi-objective constrained optimization of Composite Wing Structure

Application research in Multi-objective Constrained Optimiza...

引用

作者： He Yan Cheng JiaLin MAO Sen Zhang WeiJing AIRCRAFT INDUSTRIAL (GROUP) CO.LTD. AVIC CHENG'DU

In order to explore the optimization of composite wing structure,this paper reviews the past research works of optimization of composite wing structures worldwide and in *** concludes that most optimization methods and calculations are useful but only applied with specified theoretic *** relevant composite optimization theories and strength constraints with composite lamination failure criteria,stability,aeroelasticity are sorts *** algorithm and applied solution rounding strategy are also *** on weight-reduction analysis on the thickness,sequence,and angle of the composite stacking under multiple constraints,a practical model of a composite wing structure example with a large aspect ratio is completed,and the calculation is based on the finite element analysis tool Nastran and the genetic algorithm Matlab *** optimal solutions are given with detailed differences and the comparison of the composite structure parameters before and after calculation is also *** application example indicates the feasibility of the optimization method and quadratic rounding process,the detail structure performance improvements with skin lamination change under the calculation are illustrated at the same time.

关键词： Composite stacking Wing box structure Genetic algorithm multi-objective constrained optimization

来源：评论

学校读者我要写书评

暂无评论

Chaos Particle Swarm optimization Algorithm for multi-objective constrained optimization Problems

Chaos Particle Swarm Optimization Algorithm for Multi-Object...

引用

2010 4th International Conference on Intelligent Information Technology Application (IITA2010)

作者： Dekun Tan Department of Computer Science & Technolog,Nanchang Institute of Technology Nanchang,Jiangxi Province,China 330099

In this paper,an improved particle swarm algorithm based on chaos for multi-objective optimization problems is *** algorithm uses external archive to save the current best solutions,and maintains the archive by density distance,the object dynamic crowding is used to measure Pareto solutions' quality and the strategy of eliminating low dynamic crowding solutions is employed to enhance non-dominated solutions *** order to preserve population diversity,the global best is selected randomly from those non-dominated solutions which have bigger density distance in the *** best position is updated by Pareto dominance *** the basic particle swarm optimization gets into local convergence,chaos disturbance is introduced to guide the swarm to escape from local optima,so it can overcome the defect of traditional particle swarm optimization algorithm on getting into local best and enhance the global exploratory capability of *** proposed algorithm is compared with two well known multi-objective evolutionary algorithms through three standard test functions,the numerical experiment results demonstrate that the obtained Pareto optimal solutions by the algorithm can rapidly converge to the Pareto front and uniformly spread along the front.

关键词： multi-objective constrained optimization chaos particle swarm optimization pareto solutions external archive density distance

来源：评论

学校读者我要写书评

暂无评论

RESEARCH ON A multi-objective constrained optimization EVOLUTIONARY ALGORITHM

RESEARCH ON A MULTI-OBJECTIVE CONSTRAINED OPTIMIZATION EVOLU...

引用

2016 4th IEEE International Conference on Cloud Computing and Intelligence Systems（IEEE CCIS2016）

作者： Jiapeng Xiu Qun He Zhengqiu Yang Chen Liu Beijing University of Posts and Telecommunications

ISBN: (纸本)9781509012572

To overcome the defects of partial multi-objective constrained optimization evolutionary algorithms especially in getting local optimal solutions,poor diversity and robustness,a hybrid algorithm which is named NCCMOEA(Non-dominated Clonal constrained multi-objective optimization Evolutionary Algorithm) is proposed in this *** new algorithm combines the Pareto constrained-dominance,improved stochastic ranking algorithm and clone method in immune multi-objective optimization *** show that compared with the other effective algorithms,this algorithm NCCMOEA is more excellent in diversity and robustness and avoid getting local optimal solutions obviously.

关键词： multi-objective constrained optimization multi-objective constrained optimization Evolutionary Algorithm NCCMOEA

来源：评论

学校读者我要写书评

暂无评论

Relative assessment of constrained multiple objective optimization techniques for optimal pumping strategy design to mitigate saline water intrusion in coastal groundwater systems

引用

DESALINATION 2025年 606卷

作者： Roy, Dilip Kumar Datta, Bithin Bangladesh Agr Res Inst Irrigat & Water Management Div Gazipur 1701 Bangladesh James Cook Univ Coll Sci & Engn 1 James Cook Dr Douglas Qld 4814 Australia

Saltwater intrusion (SWI) degrades water quality in coastal groundwater systems. Over-abstraction from these aquifers accelerates SWI, necessitating practical measures to prevent it and enable sustainable extraction of groundwater resources. Simulation-optimization (S/O) methods have been widely adopted for developing optimized groundwater extraction strategies, with optimization algorithms playing a critical role. This study compared several constrained multi-objective optimization algorithms (CMOOAs) for designing pumping schemes to mitigate SWI in coastal aquifers. The evaluated algorithms included the Controlled Elitist multi- objective Genetic Algorithm (CEMOGA), multi-objective Feasibility Enhanced Particle Swarm optimization (MOFEPSO), multi-objective Lichtenberg Algorithm (MOLA), and multi-objective Pareto Search (MOPS). A biobjective SWI management model was developed using an S/O approach, with the FEMWATER code replaced by a surrogate model based on multivariate Adaptive Regression Spline (MARS) to improve computational efficiency. The MARS model effectively captured aquifer processes, demonstrating strong correlation metrics (R = 0.986-0.999) and low error indicators (NRMSE = 0.001-0.019, MAE = 0.522-6.291 mg/l). This surrogate model was integrated with each CMOOA to design optimal pumping strategies that maximize beneficial abstraction while minimizing SWI. multiple independent MARS-assisted optimization runs were conducted for a robust comparison of solution accuracy and convergence time. Results showed that MARS-CEMOGA outperformed other algorithms, delivering the highest solution quality and computational efficiency, requiring just 323.86 s compared to 388.12 s for MOPS, 999.18 s for MOFEPSO, and 2316.55 s for MOLA. The study demonstrates that MARS-CEMOGA is a highly efficient tool for developing SWI management models in coastal aquifers, although other CMOOAs also produced satisfactory results.

关键词： Coastal aquifer Saltwater intrusion Coupled simulation-optimization Surrogate model multi-objective constrained optimization

来源：评论

学校读者我要写书评

暂无评论

Two-stage coevolutionary constrained multi-objective optimization algorithm for solving optimal power flow problems with wind power and FACTS devices

引用

RENEWABLE ENERGY 2024年 232卷

作者： Zhu, Jun-Hua Wang, Jie-Sheng Zheng, Yue Zhang, Xing-Yue Liu, Xun Wang, Xiao-Tian Zhang, Song-Bo Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan Liaoning Peoples R China

As a large amount of wind energy is integrated into the grid, the randomness it brings poses a challenge to modern power systems. The application of Flexible AC Transmission Systems (FACTS) in the grid is becoming more and more common, and it is necessary to consider how to choose suitable equipment in the appropriate locations. In this paper, a multi-objective optimal power flow (MOOPF) model with wind farms and FACTS devices is established. The Weibull probability density function is used to establish the wind speed model, and the cost problem brought by wind power is considered. The locations and ratings of thyristor-controlled series compensators, thyristor-controlled phase shifters, and static VAR compensators are added to the system as control variables. In addition, the constraints on the prohibited operating areas of thermal power generators and the valve point effect are also considered. Coevolutionary constrained multi-objective optimization algorithm (CCMO) is an advanced technology, and this paper improves it and names it two-stage coevolutionary constrained multi-objective optimization algorithm (TSCCMO). The proposed algorithm uses the constraint violation value as an additional objective function in the sub-population environmental selection process, and integrates a neighborhood selection strategy into the mating selection process. The population evolution process is divided into two stages, in the first stage the two populations cooperate weakly, and in the second stage the two populations will have strong cooperation. TSCCMO is used to solve this complex constrained MOOPF problem, and its results are compared and analyzed with CCMO, NSGA-II-CDP, C3M, and PPS. The comprehensive performance of TSCCMO is the best among the 6 cases.

关键词： Optimal power flow Wind energy FACTS multi-objective constrained optimization Coevolution

来源：评论

学校读者我要写书评

暂无评论

A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results

引用

SWARM AND EVOLUTIONARY COMPUTATION 2021年 67卷 100961-100961页

作者： Kumar, Abhishek Wu, Guohua Ali, Mostafa Z. Luo, Qizhang Mallipeddi, Rammohan Suganthan, Ponnuthurai Nagaratnam Das, Swagatam Kyungpook Natl Univ Dept Artificial Intelligence Daegu 41566 South Korea Cent South Univ Sch Traff & Transportat Engn Changsha 410075 Peoples R China Jordan Univ Sci & Technol Sch Comp Informat Syst Irbid 22110 Jordan Kyungpook Natl Univ Sch Elect Engn Dept Artificial Intelligence Daegu 41566 South Korea Nanyang Technol Univ Sch Elect Elect Engn Singapore 639798 Singapore Indian Stat Inst Elect & Commun Sci Unit Kolkata India

Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the performance of metaheuristics. However, these SBPs may include various unrealistic properties. As a consequence, performance assessment may lead to underestimation or overestimation. To address this issue, few benchmark suites containing real-world problems have been proposed for all kinds of metaheuristics except for constrained multi-objective Metaheuristics (CMOMs). To fill this gap, we develop a benchmark suite of Real-world constrained multi-objective optimization Problems (RWCMOPs) for performance assessment of CMOMs. This benchmark suite includes 50 problems collected from various streams of research. We also present the baseline results of this benchmark suite by using state-of-the-art algorithms. Besides, for comparative analysis, a ranking scheme is also proposed.

关键词： Metaheuristics Performance assessment Real-World problems multi-objective constrained optimization Benchmark-Suite Ranking scheme

来源：评论

学校读者我要写书评

暂无评论

A multi-objective problem based on fuzzy inference with application to parametric design of an electrophotographic system

引用

EXPERT SYSTEMS WITH APPLICATIONS 2011年第7期38卷 8673-8683页

作者： Chen, Cheng-Lun Weng, Ching-Pang Natl Chung Hsing Univ Dept Elect Engn Taichung 40227 Taiwan

This paper proposes a systematic approach to conduct system-level optimal parametric design for a class of electrophotographic systems. A conventional monochrome laser printer serves as the platform for verification of the proposed optimal design approach. Besides performance, we incorporate two other practical indices, i.e., cost and energy consumption, into design objectives and formulate a multi-objective optimization problem. A fuzzy inference system is established to provide the nonlinear or linguistic mapping between the decision variables and the design objectives. For comparative purpose, the problem is solved using both single-objective and multi-objective optimization algorithms. Note that the proposed approach is also applicable to other complex systems. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Fuzzy inference system Genetic algorithm Electrophotographic system multi-objective constrained optimization

来源：评论

学校读者我要写书评

暂无评论

Optimal parameter design for an electrophotographic system using fuzzy multi-objective genetic algorithm

引用

JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS 2011年第3期34卷 367-382页

作者： Weng, Ching-Pang Chen, Cheng-Lun Natl Chung Hsing Univ Dept Elect Engn Taichung 40227 Taiwan

This article proposes a systematic approach to conduct system level optimal parameter design for electrophotographic systems. A conventional monochrome laser printer serves as the platform for verification of the proposed optimal design approach. Besides performance, we incorporate two other practical indices, i.e., cost and energy consumption, into design objectives and formulate a multi-objective optimization problem. Fuzzy logics are employed to provide the nonlinear or linguistic mapping between the decision variables and the design objectives. For comparison, the problem is solved using both single-objective and multi-objective optimization algorithms. Note that the proposed approach is also applicable to other complex systems.

关键词： fuzzy system genetic algorithm electrophotographic system multi-objective constrained 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：