检索结果-内蒙古大学图书馆

A Self-adaptive genetic algorithm Based on the Principle of Searching for Things

JOURNAL OF COMPUTERS 2010年第4期5卷 646-653页

作者： Zhang, Guoli Wang, Siyan Li, Yang North China Elect Power Univ Coll Math & Phys Baoding Peoples R China North China Elect Power Univ Coll Comp Sci & Technol Baoding Peoples R China

This paper proposes a new self-adaptive genetic algorithm. This new algorithm divides the whole evolution process into three stages. At each stage, the new algorithm adopts different operation method. The main ideas are grading balance selection, continuous crossover operation. The new algorithm designs especially self-adaptive mutation probability according to the principle of searching for things. Numerical experiments show that the new algorithm is more effective than the comparative algorithm in realizing the high convergence precision, reducing the convergence generation and good at keeping the stability of the adaptive genetic algorithm.

关键词： adaptive genetic algorithm gray code simulated annealing grading balance continuous mutation

来源：评论

学校读者我要写书评

暂无评论

adaptive genetic algorithm for parcel hub scheduling problem with shortcuts in closed-loop sortation system

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2019年 138卷 106114-000页

作者： Chen, James C. Chen, Tzu-Li Ou, Ting-Chieh Lee, Yu-Hsin Natl Tsing Hua Univ Dept Ind Engn & Engn Management Hsinchu 30013 Taiwan Fu Jen Catholic Univ Dept Informat Management Taipei 24205 Taiwan

This paper focuses on the parcel hub scheduling problem with shortcuts (PHSPwS), which is a critical inbound scheduling problem in parcel delivery industries such as postal service. PHSPwS employs shortcuts to determine the unloading schedule of inbound trailers/trucks in the closed-loop sorting process to minimize total makespan. PHSPwS not only considers the unequal batch sizes and various arrival times of inbound trailers but most importantly, the alternative parcel routing caused by the existence of multiple shortcuts in the closed-loop sortation system. A non-linear mixed integer program model is first formulated to address this problem. Given the computational complexity of the developed model, this research further proposes an adaptive genetic algorithm (AGA) to solve PHSPwS effectively. In the proposed AGA, local search (LS) is adopted to avoid entrapment in the local optimal solution, whereas fuzzy logic control (FLC) is utilized to adjust the probability of crossover and mutation rates. Considering the changes in average fitness values of parents and offspring in two consecutive generations could enhance the searching capability of the proposed algorithm. Computational results show that AGA with LS and FLC performs the solution better and with more stability than the other algorithms.

关键词： Parcel hub scheduling problem Shortcuts adaptive genetic algorithm Local search Fuzzy logic control Closed-loop sortation system

来源：评论

学校读者我要写书评

暂无评论

An improved self-calibration approach based on adaptive genetic algorithm for position-based visual servo

引用

控制理论与应用（英文版） 2008年第3期6卷 246-252页

作者： Ding LIU Xiongjun WU Yanxi YANG School of Automation and Information Engineering Xi＇an University of Technology Xi＇an Shaanxi 710048 China Department of Automation Shanghai Jiao Tong University Shanghai 200240 China

An improved self-calibrating algorithm for visual servo based on adaptive genetic algorithm is proposed in this paper. Our approach introduces an extension of Mendonca-Cipolla and G. Chesi＇s self-calibration for the positionbased visual servo technique which exploits the singular value property of the essential matrix. Specifically, a suitable dynamic online cost function is generated according to the property of the three singular values. The visual servo process is carried out simultaneous to the dynamic self-calibration, and then the cost function is minimized using the adaptive genetic algorithm instead of the gradient descent method in G. Chesi＇s approach. Moreover, this method overcomes the limitation that the initial parameters must be selected close to the true value, which is not constant in many cases. It is not necessary to know exactly the camera intrinsic parameters when using our approach, instead, coarse coding bounds of the five parameters are enough for the algorithm, which can be done once and for all off-line. Besides, this algorithm does not require knowledge of the 3D model of the object. Simulation experiments are carried out and the results demonstrate that the proposed approach provides a fast convergence speed and robustness against unpredictable perturbations of camera parameters, and it is an effective and efficient visual servo algorithm.

关键词： Dynamic self-calibration Visual servo adaptive genetic algorithm Parameter optimizing Essential matrix Computer vision

来源：评论

学校读者我要写书评

暂无评论

Task Allocation Optimization in Collaborative Customized Product Development Based on adaptive genetic algorithm

引用

JOURNAL OF INTELLIGENT SYSTEMS 2014年第1期23卷 1-19页

作者： Bao, Beifang Yang, Yu Liu, Aijun Zhao, Jiali Li, Leiting Chongqing Univ State Key Lab Mech Transmiss Chongqing 400030 Peoples R China Xidian Univ Econ & Management Sch Xian 710071 Peoples R China Chongqing Acad Sci & Technol Chongqing 401123 Peoples R China

Due to the currently insufficient consideration of task fitness and task coordination for task allocation in collaborative customized product development, this research was conducted based on the analysis of collaborative customized product development process and task allocation strategy. The definitions and calculation formulas of task fitness and task coordination efficiency were derived, and a multiobjective optimization model of product customization task allocation was constructed. A solution based on adaptive genetic algorithm was proposed, and the feasibility and effectiveness of the task allocation algorithm were tested and verified using a 5-MW wind turbine product development project as example.

关键词： Collaborative customized product development task allocation task fitness task coordination efficiency adaptive genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

The Application of the Linear adaptive genetic algorithm to Optimal Power Flow Problem

引用

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2014年第6期39卷 4901-4909页

作者： Abusorrah, Abdullah M. King Abdulaziz Univ Fac Engn Renewable Energy Res Grp Jeddah 21413 Saudi Arabia King Abdulaziz Univ Fac Engn Elect & Comp Engn Dept Jeddah 21413 Saudi Arabia

This paper proposes a Linear adaptive genetic algorithm (LAGA) for optimal power flow (OPF) problem. The proposed approach offers faster convergence than the standard genetic algorithm. In this study, LAGA is applied to the 6-bus system and the IEEE 14-bus power system. Shunt capacitance, transformer taps and generator voltages are used as control system variables to minimize the system power loss. The output of the systems under investigation is compared with the output of a classical nonlinear optimization routine to evaluate the impact of LAGA technique to OPF. Moreover, to validate the performance of LAGA approach, a demonstration and comparison with earlier published results is presented. Simulation results are found to be effective and promising.

关键词： Optimal power flow Reactive power control adaptive genetic algorithm Optimization

来源：评论

学校读者我要写书评

暂无评论

Development of an adaptive genetic algorithm to Optimize the Problem Of Unequal Facility Location

引用

FOUNDATIONS OF COMPUTING AND DECISION SCIENCES 2022年第2期47卷 111-125页

作者： Budi, Hendrik Setia Elveny, Marischa Zhuravlev, Pavel Jalil, Abduladheem Turki Al-Janabi, Samaher Alkaim, Ayad F. Saleh, Marwan Mahmood Shichiyakh, Rustem Adamovich Sutarto Univ Airlangga Fac Dent Med Dept Oral Biol Surabaya 60132 Indonesia Univ Sumatera Utara DS & CI Res Grp Dr Mansur Rd 9 Kampus USU Medan 20155 Indonesia Plekhanov Russian Univ Econ Stremyanny Lane 36 Moscow 117997 Russia Al Mustaqbal Univ Coll Med Labs Tech Dept Babylon 51001 Hilla Iraq Univ Babylon Coll Sci Women Babylon Iraq Univ Anbar Ramadi Iraq Kuban State Agr Univ Dept Management Krasnodar 350044 Krasnodar Regio Russia Univ Pendidikan Mandalika Fac Sci Engn & Appl Math Educ Mataram Indonesia SDG1 Zero Hunger Res Cluster Landmark Univ Nigeri SDG6 Clean Energy Res Cluster Landmark Univ Omu Aran Nigeria

The problem of unequal facility location involves determining the location of a set of production equipment whose dimensions are different, as well as the interrelationships between each of them. This paper presents an efficient method for optimizing the problem of unequal facility layouts. In this method, the genetic algorithm is improved and developed into an adaptive genetic algorithm. In this algorithm, the mutation operator is applied only when the similarity of chromosomes in each population reaches a certain level. This intelligence prevents jumps in situations where they are not needed and reduces computational time. In order to measure the performance of the proposed algorithm, its performance is compared with the performance of conventional genetic algorithms and refrigeration simulators. Computational results show that the adaptive genetic algorithm is able to achieve higher-quality solutions.

关键词： Unequal Facility location Interactions adaptive genetic algorithm Mutation Operator Intelligence healthy lifestyle

来源：评论

学校读者我要写书评

暂无评论

An adaptive genetic algorithm with diversity-guided mutation and its global convergence property

引用

Journal of Central South University of Technology 2004年第3期11卷 323-327页

作者：李枚毅蔡自兴孙国荣 College of Information Science and Engineering Central South University Changsha 410083 China

An adaptive genetic algorithm with diversity-guided mutation, which combines adaptive probabilities of crossover and mutation was proposed. By means of homogeneous finite Markov chains, it is proved that adaptive genetic algorithm with diversity-guided mutation and genetic algorithm with diversity-guided mutation converge to the global optimum if they maintain the best solutions, and the convergence of adaptive genetic algorithms with adaptive probabilities of crossover and mutation was studied. The performances of the above algorithms in optimizing several unimodal and multimodal functions were compared. The results show that for multimodal functions the average convergence generation of the adaptive genetic algorithm with diversity-guided mutation is about 900 less than that of (adaptive) genetic algorithm with adaptive probabilities and genetic algorithm with diversity-guided mutation, and the adaptive genetic algorithm with diversity-guided mutation does not lead to premature convergence. It is also shown that the better balance between overcoming premature convergence and quickening convergence speed can be gotten.

关键词： diversity-guided mutation adaptive genetic algorithm Markov chain global convergence

来源：评论

学校读者我要写书评

暂无评论

Emergency dynamic alliance partner selection based on adaptive genetic algorithm 3

Emergency dynamic alliance partner selection based on adapti...

引用

3rd Asian Pacific Conference on Mechanical Components and Control Engineering (ICMCCE)

作者： Hu, Min Beijing Informat Sci & Technol Univ Sch Informat Management Beijing Peoples R China

ISBN: (纸本)9783038353126

Emergency mobilization alliance partner selection process is longitudinally choice of the value chain to achieve a task. Value of subtasks coefficient has been discussed. Depending on the difficulty of the problem and analytical perspective, the model of emergency mobilization alliance partner selection is given to maximize the overall effectiveness of the emergency mobilization. The choice of partner selection using adaptive genetic algorithm is made and the comparison with other methods has been analyzed.

关键词： emergency dynamic alliance adaptive genetic algorithm partner selection

来源：评论

学校读者我要写书评

暂无评论

Solving Call Center Agent Scheduling Problem through Improved adaptive genetic algorithm

Solving Call Center Agent Scheduling Problem through Improve...

引用

5th International Symposium on Computational Intelligence and Design (ISCID)

作者： Ma, Yue Liu, Lieli Beijing Univ Aeronaut & Astronaut Sch Econ & Management Beijing 10091 Peoples R China

ISBN: (纸本)9780769548111

With the emergence of call center and its wide applications in enterprises, the schedule of agents becomes a core problem for reasonably deploying the human resources in call center and improving the productive force of the call center. This study uses improved adaptive genetic algorithm (IAGA) to solve scheduling problem for a 24-hours call center. This paper builds a mathematical model to describe the constraints of the agent scheduling problem with the object for minimizing the gap between demand forecast and actual work volume in each time period. In order to solve the defects of existing search algorithm, this paper uses IAGA to get the optimal solution of the optimization problem. Satisfactorily, the simulation results have turned out that the method possesses a better solving effect in faster test speed.

关键词： call center scheduling genetic algorithm adaptive genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

adaptive genetic algorithm Based Multi-Objective Optimization for Photovoltaic Cell Design Parameter Extraction

引用

Energy Procedia 2017年 117卷 432-441页

作者： P. Ashwini Kumari P. Geethanjali School of Electrical Engineering VIT University Vellore 632009 REVA University Bangalore 560064 India School of Electrical Engineering VIT University Vellore 632009 India

In this paper, an enhanced evolutionary computing algorithm has been attempted for photo voltaic (PV) design parameter extraction using adaptive genetic algorithm. The I-V curve fitting approach has been used to find optimal photovoltaic parameters Unlike single objective function based approaches, multiple objective functions including, least mean square error and Pearson residual error optimization are considered to fit the I-V curve. A cumulative fitness function is derived using both objectives that alleviate computational complexity, local minima and convergence. Importantly, Pearson residual error optimization (PRO) optimizes least mean square error (LSE) reduction while alleviating the probability of under/over-fitting that ensures optimal PV design parameter identification

关键词： PV Design Parameter Extraction adaptive genetic algorithm Multi-Objective Optimization I-V Curve Fitting

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：