检索结果-内蒙古大学图书馆

28th Chinese Control and Decision Conference

作者： Cheng, Gang Lv, Chao Yan, Shi Xu, Li Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China Akita Prefectural Univ Dept Elect & Informat Syst Akita 0150055 Japan

ISBN: (纸本)9781467397148

In this paper, a novel hybrid optimization algorithm named BBO-PSO is proposed, which is a combination of biogeography-based optimization (BBO) and particle swarm optimization (PSO). In this optimization algorithm, BBO will be employed for local search while PSO will be employed for global search, which makes the algorithm possess powerful search ability in the solution space. The proposed algorithm and 3 existing optimization algorithms are tested on 6 well known benchmarks and the simulation results show that BBO-PSO has better performance than the others.

关键词： hybrid optimization algorithm Particle Swarm optimization Biogeography-Based optimization

来源：评论

学校读者我要写书评

暂无评论

Optimal Power Flow Using a hybrid optimization algorithm of Particle Swarm optimization and Gravitational Search algorithm

引用

ELECTRIC POWER COMPONENTS AND SYSTEMS 2015年第17期43卷 1958-1970页

作者： Radosavljevic, Jordan Klimenta, Dardan Jevtic, Miroljub Arsic, Nebojsa Univ Pristina Kosovska Mitrovica Fac Tech Sci Kosovska Mitrovica 38220 Serbia

This article presents a hybrid algorithm based on the particle swarm optimization and gravitational search algorithms for solving optimal power flow in power systems. The proposed optimization technique takes advantages of both particle swarm optimization and gravitational search algorithms by combining the ability for social thinking in particle swarm optimization with the local search capability of the gravitational search algorithm. Performance of this approach for the optimal power flow problem is studied and evaluated on standard IEEE 30-bus and IEEE 118-bus test systems with different objectives that reflect fuel cost minimization, voltage profile improvement, voltage stability enhancement, power loss reduction, and fuel cost minimization with consideration of the valve point effect of generation units. Simulation results show that the hybrid particle swarm optimization-gravitational search algorithm provides an effective and robust high-quality solution of the optimal power flow problem.

关键词： optimal power flow particle swarm optimization gravitational search algorithm hybrid optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A Novel hybrid optimization algorithm Combined with BBO and PSO

A Novel Hybrid Optimization Algorithm Combined with BBO and ...

引用

第28届中国控制与决策会议

作者： Gang Cheng Chao Lv Shi Yan Li Xu School of Information Science and Engineering Lanzhou University Department of Electronics and Information Systems Akita Prefectural University

ISBN: (纸本)9781467397155

In this paper,a novel hybrid optimization algorithm named BBO-PSO is proposed,which is a combination of biogeography-based optimization(BBO) and particle swarm optimization(PSO).In this optimization algorithm,BBO will be employed for local search while PSO will be employed for global search,which makes the algorithm possess powerful search ability in the solution *** proposed algorithm and 3 existing optimization algorithms are tested on 6 well known benchmarks and the simulation results show that BBO-PSO has better performance than the others.

关键词： hybrid optimization algorithm Particle Swarm optimization Biogeography-Based optimization

来源：评论

学校读者我要写书评

暂无评论

A hybrid optimization algorithm for Pairwise Test Suite Generation

A Hybrid Optimization Algorithm for Pairwise Test Suite Gene...

引用

IEEE International Conference on Information and Automation 2015

作者： Qi, Rongzhi Wang, Zhijian Ping, Ping Li, Shuiyan Hohai Univ Coll Comp & Informat Nanjing Jiangsu Peoples R China Hohai Univ Coll Sci Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781467391047

Pairwise testing is an effective combinatorial test generation technique that can generate relative small test suite to cover all pairs of parameter values at least once. Genetic algorithm has been used for pairwise test suite generation by some researchers. In order to improve the performance of genetic algorithm, this paper proposes a hybrid optimization algorithm by augmenting genetic algorithm with two-stage hill climbing. The first stage is to improve all the individuals after genetic operations. The second stage is to improve the best solution of the current generation at the end of each generation. A series of experiments are conducted to evaluate the proposed algorithm. Experiment results show that the proposed algorithm is very competitive with respect to other approaches reported in the literature.

关键词： pairwise testing hybrid optimization algorithm genetic algorithm hill climbing

来源：评论

学校读者我要写书评

暂无评论

A hybrid algorithm and collaborative optimization strategy based on novel coding method for SPRD

引用

OCEAN ENGINEERING 2024年第Part1期311卷

作者： Yan, Wei-qiang Yang, Zhi-yao Yu, Yan-yun Lin, Yan Dalian Univ Technol Sch Naval Architecture & Ocean Engn Dalian 116024 Peoples R China

In previous research on ship pipe routing algorithms, the pipe coding methods always express pipes as straight segments. However, in actual design, pipes often need to be bent for space conservation, safety, or other reasons. Representing pipes only as straight segments deviates significantly from reality. Thus, this paper proposes a novel pipe coding method based on grid-free space, which can accurately represent a complete pipe composed of straight segments and bends. Additionally, we introduced Square strategy (SQS) into Differential Evolution strategy (DE) resulting in a novel signal objective hybrid algorithm called SQDE with high computational efficiency and strong global optimization ability. Furthermore, traditional ship pipe optimization focuses solely on the pipe itself, but considering both the pipe and its connected equipment during the optimization process can further improve the design quality of the entire pipe system. Therefore, we propose a novel cooperation optimization strategy based on a three-dimensional environment to enhance the design quality of the entire pipe system. Finally, the feasibility and reliability of the proposed approaches have been demonstrated through three simulation experiments.

关键词： hybrid optimization algorithm Ship pipe route design Coding technology Collaborative optimization

来源：评论

学校读者我要写书评

暂无评论

Parameter optimization of electromagnetic suspension-type maglev train control system based on multi-objective grey wolf non-dominated sorting hybrid algorithm-II hybrid algorithm

引用

JOURNAL OF LOW FREQUENCY NOISE VIBRATION AND ACTIVE CONTROL 2024年第2期43卷 956-978页

作者： Wang, Meiqi Zeng, Siheng Liu, Pengfei He, Yixin Chen, Enli Shijiazhuang Tiedao Univ State Key Lab Mech Behav & Syst Safety Traff Engn Shijiazhuang Peoples R China Shijiazhuang Tiedao Univ Sch Mech Engn Shijiazhuang Peoples R China Shijiazhuang Tiedao Univ Hebei Prov Key Lab Engn Machinery Power & Transmis Shijiazhuang Peoples R China Shijiazhuang Tiedao Univ State Key Lab Mech Behav & Syst Safety Traff Engn 17 NortheastInner Ring 2 Shijiazhuang 050043 Hebei Peoples R China

This paper presents a novel hybrid algorithm based on CMOGWO-ADNSGA-II to solve the vibration stability problem during the operation of a EMS-type maglev train dynamics model subjected to strong non-linear magnetic buoyancy. The proposed algorithm optimizes the control system parameters of EMS-type maglev train suspensions by combining an improved multi-objective chaotic grey wolf algorithm (CMOGWO) with an improved non-dominated Sorting genetic algorithm-II (ADNSGA-II) to enhance the search capability of the algorithm and ensure population diversity. The efficacy of the algorithm is demonstrated by applying it to the EMS-type maglev train suspension frame control system to find the optimal control parameters. Experimental results show that the system with the optimal parameters applied significantly reduces the suspension gap amplitude and the corresponding standard deviation, as well as the vertical acceleration amplitude and the corresponding standard deviation during operation. The proposed algorithm provides a good solution for EMS-type maglev train suspension vibration control, which can improve its performance and safety.

关键词： electromagnetic suspension-type maglev trains hybrid optimization algorithm vibration control non-linear magnetic buoyancy multi-objective problem

来源：评论

学校读者我要写书评

暂无评论

optimization of staggered peak intermittent pumping operation scheduling of pumping unit well clusters under wind, solar and energy storage microgrid with improved adaptive GAPSO hybrid algorithm

GEOENERGY SCIENCE AND ENGINEERING

引用

GEOENERGY SCIENCE AND ENGINEERING 2025年 252卷

作者： Wang, Jun Tan, Chaodong Chen, Peiyao Lu, Mei Feng, Gang Gao, Xiaoyong Liu, Bin Jing, Linru China Univ Petr Coll Artificial Intelligence Beijing 102249 Peoples R China CNPC Changging Oilfield Co Res Inst Oil & Gas Technol Xian 710000 Shanxi Peoples R China Xian Supcon World Technol Dev Co Ltd Xian 710016 Shanxi Peoples R China

Using manual experience-developed intermittent pumping systems for clustered wells in low-permeability reservoirs in the middle and late stages of production often leads to problems such as high operating costs. After the wind and photovoltaic power generation is introduced into the intermittent pumping system of pumping well clusters, the system faces deficiencies such as low consumption capacity of green power. For this reason, with the objectives of the lowest daily operating cost (including the operation and maintenance cost of the source-side equipment, the power purchase cost and the power sale revenue generated from the interaction with the grid) and the highest green power consumption rate of the intermittent pumping system, an optimization model for the staggered peak intermittent pumping operation and scheduling of pumping well clusters under Wind, Solar and Energy Storage microgrids was established by taking into account the power constraints of the devices at the source side and the production constraints of the wells at the load side. The improved adaptive GAPSO hybrid algorithm is used to solve the model. Compared with the results of the traditional optimization algorithm, the daily operation cost of the scheduling scheme solved by the improved algorithm is reduced from RMB 170 to RMB 150, the green power consumption rate is increased from 83 % to 86 %, and the daily production of the well cluster is also increased by 4.86 %. The case study shows that the proposed model can effectively improve the system's green power consumption capacity by adjusting the charging and discharging power of the storage battery and the power purchased and sold from the grid, and minimizing the system's daily operating cost while ensuring that the pumping well cluster meets the production demand. All simulations are performed in MATLAB by a computer with a 13th Gen Intel(R) Core(TM) i5-13500H CPU at 2.60 GHz with 16 GB of RAM.

关键词： Wind and photovoltaic power generation Pumping unit well cluster Staggered peak intermittent pumping operation Optimal scheduling hybrid optimization algorithm Genetic algorithm and particle swamp optimization

来源：评论

学校读者我要写书评

暂无评论

Optimal operation of single and multi-reservoir systems via hybrid shuffled grey wolf optimization algorithm (SGWO)

引用

WATER SUPPLY 2022年第2期22卷 1663-1675页

作者： Masoumi, Fariborz Masoumzadeh, Sina Zafari, Negin Emami-Skardi, Mohammad Javad Univ Mohaghegh Ardabili Dept Civil Engn Ardebil Iran Univ Tabriz Fac Civil Engn Tabriz Iran Univ Tehran Sch Civil Engn Coll Engn Tehran Iran

Reservoir operation is a key issue in the water resources system. In this paper, the Shuffled Grey Wolf Optimizer (SGWO), a hybrid optimization algorithm inspired by Shuffled Complex Evolution (SCE-UA) and Gray Wolf Optimizer (GWO) algorithms, is introduced. The main modification in the proposed algorithm is how it divides and shuffles the population to enhance the information exchange among the individuals. The performance of the SGWO algorithm is compared to famous evolutionary algorithms such as Particle Swarm optimization (PSO) and Genetic algorithm (GA) in solving mathematical benchmark functions and multiple types of reservoir operation optimization problems with different scales. Two hypothetical 4 and10-reservoir system, and the Dez dam in Iran as a single reservoir system were selected as the case study in this research. The capability of the algorithms was compared in terms of accuracy of derived optimum objective function values, convergence speed, and stability of answers in different implementations. The results showed that the SGWO can reach considerably better results (0.3% to 26% better than the closest rival algorithms) using significantly lower number of function evaluations. It also showed the lowest standard deviation among other algorithms for all problems, which indicated the high reliability of this algorithm.

关键词： Grey Wolf optimization (GWO) hybrid optimization algorithm meta-heuristic algorithms reservoir operation shuffled complex evolution (SCE)

来源：评论

学校读者我要写书评

暂无评论

Minimization of a Cogging Torque for an Interior Permanent Magnet Synchronous Machine using a Novel hybrid optimization algorithm

引用

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2014年第3期9卷 859-865页

作者： Kim, Il-Woo Woo, Dong-Kyun Lim, Dong-Kuk Jung, Sang-Yong Lee, Cheol-Gyun Ro, Jong-Suk Jung, Hyun-Kyo Seoul Natl Univ Seoul South Korea Hyosung Corp Changwon Plant Special Motor Design Team Seoul South Korea Seoul Natl Univ Dept Elect & Comp Engn Seoul South Korea Sungkyunkwan Univ Sch Elect & Elect Engn Seoul South Korea Dong Eui Univ Pusan South Korea

optimization of an electric machine is mainly a nonlinear multi-modal problem. For the optimization of the multi-modal problem, many function calls are required with much consumption of time. To address this problem, this paper proposes a novel hybrid algorithm in which function calls are less than conventional methods. Specifically, the proposed method uses the kriging metamodel and the fill-blank technique to find an approximated solution in a whole problem region. To increase the convergence speed in local peaks, a parallel gradient assisted simplex method is proposed and combined with the kriging meta-model. The correctness and usefulness of the proposed hybrid algorithm is verified through a mathematical test function and applied into the practical optimization as the cogging torque minimization for an interior permanent magnet synchronous machine.

关键词： hybrid optimization algorithm Kriging Motor optimization Permanent magnet machine Simplex

来源：评论

学校读者我要写书评

暂无评论

Development of hybrid performance-based optimization algorithm for structures equipped with vibration damper devices

引用

ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING 2023年第2期23卷 123-123页

作者： Ayyash, Al-jbury Najad Amer Hejazi, Farzad Univ Putra Malaysia Dept Civil Engn Seri Kembangan Malaysia Univ West England Fac Environm & Technol Bristol England

Nowadays, various types of vibration damping systems are being implemented in different buildings to diminish seismic effects on structures. However, engineers are faced with the challenging task of developing an optimum design for structures utilizing a proper type of damping device based on new techniques such as the performance-based design method. Therefore, this research was aimed at developing a multi-objective optimization algorithm by hybridizing the particle swarm optimization (PSO) and gravitational search algorithm (GSA) to obtain an optimum design for structures equipped with vibration damper devices based on the performance-based design method. Then, the developed hybrid algorithm (PSOGSA) would be capable of optimizing the damping system simultaneously with the optimized details of the structural sections, including the steel rebars, by satisfying all the design criteria. For this purpose, a special process for the design of structures equipped with vibration damper devices according to the performance-based design method was developed by considering of a wide range of vibration damping systems. The proposed PSOGSA optimization framework was then implemented to design a 12-storey reinforced concrete structure equipped with different types of dampers to minimize the structural weight while satisfying all the prescribed performance-based design acceptance criteria. The results indicated that the proposed optimization method was able to successfully optimize the details of the structural members as well as the type and properties of the damper, which significantly improved the structural response in terms of the formation of plastic hinges and the structural movements.

关键词： hybrid optimization algorithm Particle swarm optimization Gravitational search algorithm Seismic damper devices Performance-based design

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：