期刊文献+
共找到59篇文章
< 1 2 3 >
每页显示 20 50 100
A New Evolutionary Algorithm for Function Optimization 被引量:37
1
作者 GUO Tao, KANG Li shan State Key Laboratory of Software Engineering, Wuhan University,Wuhan 430072, China 《Wuhan University Journal of Natural Sciences》 CAS 1999年第4期409-414,共6页
A new algorithm based on genetic algorithm(GA) is developed for solving function optimization problems with inequality constraints. This algorithm has been used to a series of standard test problems and exhibited good... A new algorithm based on genetic algorithm(GA) is developed for solving function optimization problems with inequality constraints. This algorithm has been used to a series of standard test problems and exhibited good performance. The computation results show that its generality, precision, robustness, simplicity and performance are all satisfactory. 展开更多
关键词 Key words evolutionary algorithm function optimization problem inequality constraints
下载PDF
A Parallel Global-Local Mixed Evolutionary Algorithm for Multimodal Function Optimization Based on Domain Decomposition 被引量:4
2
作者 Wu Zhi-jian, Tang Zhi-long,Kang Li-shanState Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei, China 《Wuhan University Journal of Natural Sciences》 CAS 2003年第S1期253-258,共6页
This paper presents a parallel two-level evolutionary algorithm based on domain decomposition for solving function optimization problem containing multiple solutions. By combining the characteristics of the global sea... This paper presents a parallel two-level evolutionary algorithm based on domain decomposition for solving function optimization problem containing multiple solutions. By combining the characteristics of the global search and local search in each sub-domain, the former enables individual to draw closer to each optima and keeps the diversity of individuals, while the latter selects local optimal solutions known as latent solutions in sub-domain. In the end, by selecting the global optimal solutions from latent solutions in each sub-domain, we can discover all the optimal solutions easily and quickly. 展开更多
关键词 function optimization GT algorithm GLME algorithm evolutionary algorithm domain decomposition
下载PDF
Interface Design and Functional Optimization of Chinese Learning Apps Based on User Experience
3
作者 Qihui Hong Jialing Hu Nianxiu Fang 《教育技术与创新》 2024年第2期59-78,共20页
This research paper investigates the interface design and functional optimization of Chinese learning apps through the lens of user experience.With the increasing popularity of Chinese language learning apps in the er... This research paper investigates the interface design and functional optimization of Chinese learning apps through the lens of user experience.With the increasing popularity of Chinese language learning apps in the era of rapid mobile internet development,users'demands for enhanced interface design and interaction experience have grown significantly.The study aims to explore the influence of user feedback on the design and functionality of Chinese learning apps,proposing optimization strategies to improve user experience and learning outcomes.By conducting a comprehensive literature review,utilizing methods such as surveys and user interviews for data collection,and analyzing user feedback,this research identifies existing issues in the interface design and interaction experience of Chinese learning apps.The results present user opinions,feedback analysis,identified problems,improvement directions,and specific optimization strategies.The study discusses the potential impact of these optimization strategies on enhancing user experience and learning outcomes,compares findings with previous research,addresses limitations,and suggests future research directions.In conclusion,this research contributes to enriching the design theory of Chinese learning apps,offering practical optimization recommendations for developers,and supporting the continuous advancement of Chinese language learning apps. 展开更多
关键词 Chinese Learning Apps User Experience Interface Design functional optimization
下载PDF
An Improved Harris Hawk Optimization Algorithm
4
作者 GuangYa Chong Yongliang YUAN 《Mechanical Engineering Science》 2024年第1期21-25,共5页
Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).F... Aiming at the problems that the original Harris Hawk optimization algorithm is easy to fall into local optimum and slow in finding the optimum,this paper proposes an improved Harris Hawk optimization algorithm(GHHO).Firstly,we used a Gaussian chaotic mapping strategy to initialize the positions of individuals in the population,which enriches the initial individual species characteristics.Secondly,by optimizing the energy parameter and introducing the cosine strategy,the algorithm's ability to jump out of the local optimum is enhanced,which improves the performance of the algorithm.Finally,comparison experiments with other intelligent algorithms were conducted on 13 classical test function sets.The results show that GHHO has better performance in all aspects compared to other optimization algorithms.The improved algorithm is more suitable for generalization to real optimization problems. 展开更多
关键词 Harris Hawk optimization algorithm chaotic mapping cosine strategy function optimization
下载PDF
Adaptive immune-genetic algorithm for global optimization to multivariable function 被引量:9
5
作者 Dai Yongshou Li Yuanyuan +2 位作者 Wei Lei Wang Junling Zheng Deling 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第3期655-660,共6页
An adaptive immune-genetic algorithm (AIGA) is proposed to avoid premature convergence and guarantee the diversity of the population. Rapid immune response (secondary response), adaptive mutation and density opera... An adaptive immune-genetic algorithm (AIGA) is proposed to avoid premature convergence and guarantee the diversity of the population. Rapid immune response (secondary response), adaptive mutation and density operators in the AIGA are emphatically designed to improve the searching ability, greatly increase the converging speed, and decrease locating the local maxima due to the premature convergence. The simulation results obtained from the global optimization to four multivariable and multi-extreme functions show that AIGA converges rapidly, guarantees the diversity, stability and good searching ability. 展开更多
关键词 immune-genetic algorithm function optimization hyper-mutation density operator.
下载PDF
Dipper Throated Optimization Algorithm for Unconstrained Function and Feature Selection 被引量:4
6
作者 Ali E.Takieldeen El-Sayed M.El-kenawy +1 位作者 Mohammed Hadwan Rokaia M.Zaki 《Computers, Materials & Continua》 SCIE EI 2022年第7期1465-1481,共17页
Dipper throated optimization(DTO)algorithm is a novel with a very efficient metaheuristic inspired by the dipper throated bird.DTO has its unique hunting technique by performing rapid bowing movements.To show the effi... Dipper throated optimization(DTO)algorithm is a novel with a very efficient metaheuristic inspired by the dipper throated bird.DTO has its unique hunting technique by performing rapid bowing movements.To show the efficiency of the proposed algorithm,DTO is tested and compared to the algorithms of Particle Swarm Optimization(PSO),Whale Optimization Algorithm(WOA),Grey Wolf Optimizer(GWO),and Genetic Algorithm(GA)based on the seven unimodal benchmark functions.Then,ANOVA and Wilcoxon rank-sum tests are performed to confirm the effectiveness of the DTO compared to other optimization techniques.Additionally,to demonstrate the proposed algorithm’s suitability for solving complex realworld issues,DTO is used to solve the feature selection problem.The strategy of using DTOs as feature selection is evaluated using commonly used data sets from the University of California at Irvine(UCI)repository.The findings indicate that the DTO outperforms all other algorithms in addressing feature selection issues,demonstrating the proposed algorithm’s capabilities to solve complex real-world situations. 展开更多
关键词 Metaheuristic optimization swarmoptimization feature selection function optimization
下载PDF
Elitism-based immune genetic algorithm and its application to optimization of complex multi-modal functions 被引量:4
7
作者 谭冠政 周代明 +1 位作者 江斌 DIOUBATE Mamady I 《Journal of Central South University of Technology》 EI 2008年第6期845-852,共8页
A novel immune genetic algorithm with the elitist selection and elitist crossover was proposed, which is called the immune genetic algorithm with the elitism (IGAE). In IGAE, the new methods for computing antibody s... A novel immune genetic algorithm with the elitist selection and elitist crossover was proposed, which is called the immune genetic algorithm with the elitism (IGAE). In IGAE, the new methods for computing antibody similarity, expected reproduction probability, and clonal selection probability were given. IGAE has three features. The first is that the similarities of two antibodies in structure and quality are all defined in the form of percentage, which helps to describe the similarity of two antibodies more accurately and to reduce the computational burden effectively. The second is that with the elitist selection and elitist crossover strategy IGAE is able to find the globally optimal solution of a given problem. The third is that the formula of expected reproduction probability of antibody can be adjusted through a parameter r, which helps to balance the population diversity and the convergence speed of IGAE so that IGAE can find the globally optimal solution of a given problem more rapidly. Two different complex multi-modal functions were selected to test the validity of IGAE. The experimental results show that IGAE can find the globally maximum/minimum values of the two functions rapidly. The experimental results also confirm that IGAE is of better performance in convergence speed, solution variation behavior, and computational efficiency compared with the canonical genetic algorithm with the elitism and the immune genetic algorithm with the information entropy and elitism. 展开更多
关键词 immune genetic algorithm multi-modal function optimization evolutionary computation elitist selection elitist crossover
下载PDF
A new parameter setting-based modified differential evolution for function optimization
8
作者 Sukanta Nama Apu Kumar Saha 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2020年第4期97-120,共24页
The population-based efficient iterative evolutionary algorithm(EA)is differential evolution(DE).It has fewer control parameters but is useful when dealing with complex problems of optimization in the real world.A gre... The population-based efficient iterative evolutionary algorithm(EA)is differential evolution(DE).It has fewer control parameters but is useful when dealing with complex problems of optimization in the real world.A great deal of progress has already been made and implemented in various fields of engineering and science.Nevertheless,DE is prone to the setting of control parameters in its performance evaluation.Therefore,the appropriate adjustment of the time-consuming control parameters is necessary to achieve optimal DE efficiency.This research proposes a new version of the DE algorithm control parameters and mutation operator.For the justifiability of the suggested method,several benchmark functions are taken from the literature.The test results are contrasted with other literary algorithms. 展开更多
关键词 Differential evolution evolutionary algorithm unconstrained function optimization CEC2005 benchmark functions.
原文传递
An Improved GT Algorithm for Solving Complicated Dynamic Function Optimization Problems
9
作者 ZHANG Qing LI Yan +1 位作者 KANG Zhuo KANG Lishan 《Wuhan University Journal of Natural Sciences》 CAS 2009年第5期404-408,共5页
An improved Guo Tao algorithm (IGT algorithm) is proposed for solving complicated dynamic function optimization problems, and a function optimization benchmark problem with constrained condition and two dynamic para... An improved Guo Tao algorithm (IGT algorithm) is proposed for solving complicated dynamic function optimization problems, and a function optimization benchmark problem with constrained condition and two dynamic parameters has been designed. The results achieved by IGT algorithm have been compared with the results from the Guo Tao algorithm (GT algorithm). It is shown that the new algorithm (IGT algorithm) provides better results. This preliminarily demonstrates the efficiency of the new algorithm in complicated dynamic environments. 展开更多
关键词 dynamic function optimization Guo Tao algorithm (GT algorithm) benchmark problems
原文传递
Hybrid Power Bank Deployment Model for Energy Supply Coverage Optimization in Industrial Wireless Sensor Network
10
作者 Hang Yang Xunbo Li Witold Pedrycz 《Intelligent Automation & Soft Computing》 SCIE 2023年第8期1531-1551,共21页
Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monito... Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN. 展开更多
关键词 Industrial wireless sensor network hybrid power bank deployment model:energy supply coverage optimization artificial bee colony algorithm radio frequency numerical function optimization
下载PDF
Optimization of the Dressing Parameters in Cylindrical Grinding Based on a Generalized Utility Function 被引量:2
11
作者 ALEKSANDROVA Irina 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2016年第1期63-73,共11页
The existing studies, concerning the dressing process, focus on the major influence of the dressing conditions on the grinding response variables. However, the choice of the dressing conditions is often made, based on... The existing studies, concerning the dressing process, focus on the major influence of the dressing conditions on the grinding response variables. However, the choice of the dressing conditions is often made, based on the experience of the qualified staff or using data from reference books. The optimal dressing parameters, which are only valid for the particular methods and dressing and grinding conditions, are also used. The paper presents a methodology for optimization of the dressing parameters in cylindrical grinding. The generalized utility function has been chosen as an optimization parameter. It is a complex indicator determining the economic, dynamic and manufacturing characteristics of the grinding process. The developed methodology is implemented for the dressing of aluminium oxide grinding wheels by using experimental diamond roller dressers with different grit sizes made of medium- and high-strength synthetic diamonds type AC32 and AC80. To solve the optimization problem, a model of the generalized utility function is created which reflects the complex impact of dressing parameters. The model is built based on the results from the conducted complex study and modeling of the grinding wheel lifetime, cutting ability, production rate and cutting forces during grinding. They are closely related to the dressing conditions (dressing speed ratio, radial in-feed of the diamond roller dresser and dress-out time), the diamond roller dresser grit size/grinding wheel grit size ratio, the type of synthetic diamonds and the direction of dressing. Some dressing parameters are determined for which the generalized utility fimction has a maximum and which guarantee an optimum combination of the following: the lifetime and cutting ability of the abrasive wheels, the tangential cutting force magnitude and the production rate of the grinding process. The results obtained prove the possibility of control and optimization of grinding by selecting particular dressing parameters. 展开更多
关键词 dressing conditions cylindrical grinding diamond roller dresser generalized utility function based optimization
下载PDF
Two-Phase Genetic Algorithm Applied in the Optimization of Multi-Modal Function 被引量:5
12
作者 Huang Yu-zhen, Kang Li-shan,Zhou Ai-minState Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei,China 《Wuhan University Journal of Natural Sciences》 CAS 2003年第S1期259-264,共6页
This paper presents a two-phase genetic algorithm (TPGA) based on the multi- parent genetic algorithm (MPGA). Through analysis we find MPGA will lead the population' s evol vement to diversity or convergence accor... This paper presents a two-phase genetic algorithm (TPGA) based on the multi- parent genetic algorithm (MPGA). Through analysis we find MPGA will lead the population' s evol vement to diversity or convergence according to the population size and the crossover size, so we make it run in different forms during the global and local optimization phases and then forms TPGA. The experiment results show that TPGA is very efficient for the optimization of low-dimension multi-modal functions, usually we can obtain all the global optimal solutions. 展开更多
关键词 optimization of multi-modal function genetic algorithm global optimization local optimization
下载PDF
Improvement of Cardiac Function by Dry Weight Optimization Based on Interdialysis Inferior Vena Caval Diameter(2) 被引量:2
13
作者 Shixue Hirayama Yasuhiro Ando +1 位作者 Yuji Sud Yasushi Asano 《中国血液净化》 2002年第12期1-3,共3页
关键词 CTR DBP SBP EF Improvement of Cardiac function by Dry Weight optimization Based on Interdialysis Inferior Vena Caval Diameter
下载PDF
Improvement of Cardiac Function by Dry Weight Optimization Based on Interdialysis Inferior Vena Caval Diameter (1) 被引量:1
14
作者 Shizue Hirayama Yasuhiro Ando +1 位作者 Yuji Sudo Yasushi Asano 《中国血液净化》 2002年第11期1-2,共2页
In hemodialysis (HD) patients, the diameter of the inferior vena cava (IVC) serves for evaluation of the amount of body fluid.
关键词 In Improvement of Cardiac function by Dry Weight optimization Based on Interdialysis Inferior Vena Caval Diameter BODY IVC
下载PDF
Ant colony optimization algorithm and its application to Neuro-Fuzzy controller design 被引量:11
15
作者 Zhao Baojiang Li Shiyong 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第3期603-610,共8页
An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information. The algorithm can keep good balance between accelerating convergence and averting precocity and s... An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information. The algorithm can keep good balance between accelerating convergence and averting precocity and stagnation. The results of function optimization show that the algorithm has good searching ability and high convergence speed. The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due tσ multivariable inputs, a state variable synthesis scheme is employed to reduce the number of fuzzy rules greatly. The simulation results show that the designed controller can control the inverted pendulum successfully. 展开更多
关键词 neuro-fuzzy controller ant colony algorithm function optimization genetic algorithm inverted pen-dulum system.
下载PDF
Artificial bee colony algorithm with comprehensive search mechanism for numerical optimization 被引量:5
16
作者 Mudong Li Hui Zhao +1 位作者 Xingwei Weng Hanqiao Huang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2015年第3期603-617,共15页
The artificial bee colony (ABC) algorithm is a sim- ple and effective global optimization algorithm which has been successfully applied in practical optimization problems of various fields. However, the algorithm is... The artificial bee colony (ABC) algorithm is a sim- ple and effective global optimization algorithm which has been successfully applied in practical optimization problems of various fields. However, the algorithm is still insufficient in balancing ex- ploration and exploitation. To solve this problem, we put forward an improved algorithm with a comprehensive search mechanism. The search mechanism contains three main strategies. Firstly, the heuristic Gaussian search strategy composed of three different search equations is proposed for the employed bees, which fully utilizes and balances the exploration and exploitation of the three different search equations by introducing the selectivity probability P,. Secondly, in order to improve the search accuracy, we propose the Gbest-guided neighborhood search strategy for onlooker bees to improve the exploitation performance of ABC. Thirdly, the self- adaptive population perturbation strategy for the current colony is used by random perturbation or Gaussian perturbation to en- hance the diversity of the population. In addition, to improve the quality of the initial population, we introduce the chaotic opposition- based learning method for initialization. The experimental results and Wilcoxon signed ranks test based on 27 benchmark func- tions show that the proposed algorithm, especially for solving high dimensional and complex function optimization problems, has a higher convergence speed and search precision than ABC and three other current ABC-based algorithms. 展开更多
关键词 artificial bee colony (ABC) function optimization search strategy population initialization Wilcoxon signed ranks test.
下载PDF
Asynchronous Parallel Evolutionary Algorithms for Constrained Optimizations
17
作者 Kang Li-shan Liu Pu +2 位作者 Kang Zhuo Li Yan Chen Yu-ping 《Wuhan University Journal of Natural Sciences》 EI CAS 2000年第4期406-412,共7页
Recently Guo Tao proposed a stochastic search algorithm in his PhD thesis for solving function optimization problems. He combined the subspace search method (a general multi-parent recombination strategy) with the pop... Recently Guo Tao proposed a stochastic search algorithm in his PhD thesis for solving function optimization problems. He combined the subspace search method (a general multi-parent recombination strategy) with the population hill-climbing method. The former keeps a global search for overall situation, and the latter keeps the convergence of the algorithm. Guo's algorithm has many advantages, such as the simplicity of its structure, the higher accuracy of its results, the wide range of its applications, and the robustness of its use. In this paper a preliminary theoretical analysis of the algorithm is given and some numerical experiments has been done by using Guo's algorithm for demonstrating the theoretical results. Three asynchronous parallel evolutionary algorithms with different granularities for MIMD machines are designed by parallelizing Guo's Algorithm. 展开更多
关键词 asynchronous parallel evolutionary algorithm function optimization
下载PDF
An Integer Coding Based Optimization Model for Queen Problems
18
作者 Nengfa Hu 《American Journal of Computational Mathematics》 2016年第1期32-36,共5页
Queen problems are unstructured problems, whose solution scheme can be applied in the actual job scheduling. As for the n-queen problem, backtracking algorithm is considered as an effective approach when the value of ... Queen problems are unstructured problems, whose solution scheme can be applied in the actual job scheduling. As for the n-queen problem, backtracking algorithm is considered as an effective approach when the value of n is small. However, in case the value of n is large, the phenomenon of combination explosion is expected to occur. In order to solve the aforementioned problem, queen problems are firstly converted into the problem of function optimization with constraints, and then the corresponding mathematical model is established. Afterwards, the n-queen problem is solved by constructing the genetic operators and adaption functions using the integer coding based on the population search technology of the evolutionary computation. The experimental results demonstrate that the proposed algorithm is endowed with rapid calculation speed and high efficiency, and the model presents simple structure and is readily implemented. 展开更多
关键词 Queen Problem function optimization Mathematical Model Evolutionary Computation Integer Coding
下载PDF
Two-parameters quasi-filled function algorithm for nonlinear integer programming 被引量:3
19
作者 WANG Wei-xiang SHANG You-lin ZHANG Lian-sheng 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2006年第12期2083-2087,共5页
A quasi-filled function for nonlinear integer programming problem is given in this paper. This function contains two parameters which are easily to be chosen. Theoretical properties of the proposed quasi-filled functi... A quasi-filled function for nonlinear integer programming problem is given in this paper. This function contains two parameters which are easily to be chosen. Theoretical properties of the proposed quasi-filled function are investigated. Moreover, we also propose a new solution algorithm using this quasi-filled function to solve nonlinear integer programming problem in this paper. The examples with 2 to 6 variables are tested and computational results indicated the efficiency and reliability of the pro- posed quasi-filled function algorithm. 展开更多
关键词 Integer programming Local minimizer Global minimizer Filled function Global optimization
下载PDF
THEOREMS OF PEANO'S TYPE FOR BIVARIATE FUNCTIONS AND OPTIMAL RECOVERY OF LINEAR FUNCTIONALS
20
作者 N.K. Dicheva (University of Architecture, Bulgaria) 《Analysis in Theory and Applications》 2001年第3期43-53,共11页
The best recovery of a linear functional Lf, f=f(x,y), on the basis of given linear functionals L jf,j=1,2,...,N in a sense of Sard has been investigated, using analogy of Peano's theorem. The best recovery of a ... The best recovery of a linear functional Lf, f=f(x,y), on the basis of given linear functionals L jf,j=1,2,...,N in a sense of Sard has been investigated, using analogy of Peano's theorem. The best recovery of a bivariate function by given scattered data has been obtained in a simple analytical form as a special case. 展开更多
关键词 Ky THEOREMS OF PEANO’S TYPE FOR BIVARIATE functionS AND OPTIMAL RECOVERY OF LINEAR functionALS
下载PDF
上一页 1 2 3 下一页 到第
使用帮助 返回顶部