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An Improved Genetic Algorithm for Allocation Optimization of Distribution Centers 被引量:7
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作者 钱晶 庞小红 吴智铭 《Journal of Shanghai Jiaotong university(Science)》 EI 2004年第4期73-76,共4页
This paper introduced an integrated allocation model for distribution centers (DCs). The facility cost, inventory cost, transportation cost and service quality were considered in the model. An improved genetic algorit... This paper introduced an integrated allocation model for distribution centers (DCs). The facility cost, inventory cost, transportation cost and service quality were considered in the model. An improved genetic algorithm (IGA) was proposed to solve the problem. The improvement of IGA is based on the idea of adjusting crossover probability and mutation probability. The IGA is supplied by heuristic rules too. The simulation results show that the IGA is better than the standard GA(SGA) in search efficiency and equality. 展开更多
关键词 distribution center allocation optimization improved genetic algorithm
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Improved genetic algorithm freely searching for dangerous slip surface of slope 被引量:4
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作者 万文 曹平 +1 位作者 冯涛 袁海平 《Journal of Central South University of Technology》 EI 2005年第6期749-752,共4页
Based on the slice method of the non-circular slip surface for the calculation of integral stability of slope, an improved genetic algorithm was proposed, which can freely search for the most dangerous slip surface of... Based on the slice method of the non-circular slip surface for the calculation of integral stability of slope, an improved genetic algorithm was proposed, which can freely search for the most dangerous slip surface of slope and the corresponding minimum safety factor without supposing the geometric shape of the most dangerous slip surface. This improved genetic algorithm can simulate the genetic evolution process of organisms and avoid the local minimum value compared with the classical methods. The results of engineering cases show that it is a global optimal algorithm and has many advantages, such as higher efficiency and shorter time than the simple genetic algorithm. 展开更多
关键词 slice method dangerous non-circular slip surface minimum safety factor improved genetic algorithm
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Identification of Crop Diseases Based on Improved Genetic Algorithm and Extreme Learning Machine 被引量:2
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作者 Linguo Li Lijuan Sun +2 位作者 Jian Guo Shujing Li Ping Jiang 《Computers, Materials & Continua》 SCIE EI 2020年第10期761-775,共15页
As an indispensable task in crop protection,the detection of crop diseases directly impacts the income of farmers.To address the problems of low crop-disease identification precision and detection abilities,a new meth... As an indispensable task in crop protection,the detection of crop diseases directly impacts the income of farmers.To address the problems of low crop-disease identification precision and detection abilities,a new method of detection is proposed based on improved genetic algorithm and extreme learning machine.Taking five different typical diseases with common crops as the objects,this method first preprocesses the images of crops and selects the optimal features for fusion.Then,it builds a model of crop disease identification for extreme learning machine,introduces the hill-climbing algorithm to improve the traditional genetic algorithm,optimizes the initial weights and thresholds of the machine,and acquires the approximately optimal solution.And finally,a data set of crop diseases is used for verification,demonstrating that,compared with several other common machine learning methods,this method can effectively improve the crop-disease identification precision and detection abilities and provide a basis for the identification of other crop diseases. 展开更多
关键词 CROPS disease identification extreme learning machine improved genetic algorithm
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Dynamic airspace sectorization via improved genetic algorithm 被引量:6
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作者 Yangzhou Chen Hong Bi +1 位作者 Defu Zhang Zhuoxi Song 《Journal of Modern Transportation》 2013年第2期117-124,共8页
This paper deals with dynamic airspace sectorization (DAS) problem by an improved genetic algorithm (iGA). A graph model is first constructed that represents the airspace static structure. Then the DAS problem is ... This paper deals with dynamic airspace sectorization (DAS) problem by an improved genetic algorithm (iGA). A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic. 展开更多
关键词 Dynamic airspace sectorization (DAS) improved genetic algorithm (iGA) Graph model Multiple populations Hybrid coding Sector constraints
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Improved Genetic Optimization Algorithm with Subdomain Model for Multi-objective Optimal Design of SPMSM 被引量:8
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作者 Jian Gao Litao Dai Wenjuan Zhang 《CES Transactions on Electrical Machines and Systems》 2018年第1期160-165,共6页
For an optimal design of a surface-mounted permanent magnet synchronous motor(SPMSM),many objective functions should be considered.The classical optimization methods,which have been habitually designed based on magnet... For an optimal design of a surface-mounted permanent magnet synchronous motor(SPMSM),many objective functions should be considered.The classical optimization methods,which have been habitually designed based on magnetic circuit law or finite element analysis(FEA),have inaccuracy or calculation time problems when solving the multi-objective problems.To address these problems,the multi-independent-population genetic algorithm(MGA)combined with subdomain(SD)model are proposed to improve the performance of SPMSM such as magnetic field distribution,cost and efficiency.In order to analyze the flux density harmonics accurately,the accurate SD model is first established.Then,the MGA with time-saving SD model are employed to search for solutions which belong to the Pareto optimal set.Finally,for the purpose of validation,the electromagnetic performance of the new design motor are investigated by FEA,comparing with the initial design and conventional GA optimal design to demonstrate the advantage of MGA optimization method. 展开更多
关键词 improved genetic algorithm reduction of flux density spatial distortion sub-domain model multi-objective optimal design
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Energy-Efficient Process Planning Using Improved Genetic Algorithm
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作者 Dai Min Tang Dunbing +1 位作者 Huang Zhiqing Yang Jun 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2016年第5期602-609,共8页
Nowadays,energy consumption which closely contacts with environmental impacts of manufacturing processes has been highly commented as a new productivity criterion.However,little attention has paid to the development o... Nowadays,energy consumption which closely contacts with environmental impacts of manufacturing processes has been highly commented as a new productivity criterion.However,little attention has paid to the development of process planning methods that take energy consumption into account.An energy-efficient process planning model that incorporates manufacturing time and energy consumption is proposed.For solving the problem,an improved genetic algorithm method is employed to explore the optimal solution.Finally,a case study for process planning is given.The experimental result generates interesting effort,and therefore allows improving the energy efficiency of manufacturing processes in process planning. 展开更多
关键词 energy consumption process planning improved genetic algorithm energy efficiency
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Method for Fault Feature Selection for a Baler Gearbox Based on an Improved Adaptive Genetic Algorithm
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作者 Bin Ren Dong Bai +2 位作者 Zhanpu Xue Hu Xie Hao Zhang 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2022年第3期312-323,共12页
The performance and efficiency of a baler deteriorate as a result of gearbox failure.One way to overcome this challenge is to select appropriate fault feature parameters for fault diagnosis and monitoring gearboxes.Th... The performance and efficiency of a baler deteriorate as a result of gearbox failure.One way to overcome this challenge is to select appropriate fault feature parameters for fault diagnosis and monitoring gearboxes.This paper proposes a fault feature selection method using an improved adaptive genetic algorithm for a baler gearbox.This method directly obtains the minimum fault feature parameter set that is most sensitive to fault features through attribute reduction.The main benefit of the improved adaptive genetic algorithm is its excellent performance in terms of the efficiency of attribute reduction without requiring prior information.Therefore,this method should be capable of timely diagnosis and monitoring.Experimental validation was performed and promising findings highlighting the relationship between diagnosis results and faults were obtained.The results indicate that when using the improved genetic algorithm to reduce 12 fault characteristic parameters to three without a priori information,100%fault diagnosis accuracy can be achieved based on these fault characteristics and the time required for fault feature parameter selection using the improved genetic algorithm is reduced by half compared to traditional methods.The proposed method provides important insights into the instant fault diagnosis and fault monitoring of mechanical devices. 展开更多
关键词 Fault diagnosis Feature selection Attribute reduction improved adaptive genetic algorithm
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Time-optimal trajectory planning based on improved adaptive genetic algorithm
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作者 孙农亮 王艳君 《Journal of Measurement Science and Instrumentation》 CAS 2012年第2期103-108,共6页
This paper investiga tes a trajectory planning algorithm to reduce the manipulator’s working time.A t ime-optimal trajectory planning(TOTP)is conducted based on improved ad aptive genetic algorithm(IAGA)and combined ... This paper investiga tes a trajectory planning algorithm to reduce the manipulator’s working time.A t ime-optimal trajectory planning(TOTP)is conducted based on improved ad aptive genetic algorithm(IAGA)and combined with cubic triangular Bezier spline(CTBS).The CTBS based trajectory planning we did before can achieve continuous second and third derivation,hence it meets the stability requirements of the m anipulator.The working time can be greatly reduced by applying IAGA to the puma 560 trajectory planning when considering physical constraints such as angular ve locity,angular acceleration and jerk.Simulation experiments in both Matlab and ADAMS illustrate that TOTP based on IAGA can give a time optimal result with sm oothness and stability. 展开更多
关键词 time-optimal trajectory planning(TOTP) improved adaptive genetic algorithm(IAGA) cubic triangular Bezier spline(CTBS)
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An Improved Genetic Algorithm for UWB Localization
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作者 Xianzhi Zheng 《Journal of Computer and Communications》 2022年第10期1-9,共9页
The UWB localization problem can be mapped as an optimization problem, which can be solved by genetic algorithm. In the localization process, the traditional fitness function does not include the ranging information b... The UWB localization problem can be mapped as an optimization problem, which can be solved by genetic algorithm. In the localization process, the traditional fitness function does not include the ranging information between tags, resulting in insufficient ranging information and limited improvement of the localization accuracy. In view of this, an improved genetic localization algorithm is proposed. First, a new fitness function is constructed, which not only includes the ranging information between the tag and the base station, but also the ranging information between the tags to ensure that the ranging information is fully utilized in the localization process. Then, the search method based on Brownian motion is adopted to ensure that the improved algorithm can speed up the convergence speed of the localization result. The simulation results show that, compared with the traditional genetic localization algorithm, the improved genetic localization algorithm can reduce the influence of the ranging error on the localization error and improve the localization performance. 展开更多
关键词 LOCATION improved genetic algorithm Localization Accuracy UWB
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Study on Optimization of Urban Rail Train Operation Control Curve Based on Improved Multi-Objective Genetic Algorithm
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作者 Xiaokan Wang Qiong Wang 《Journal on Internet of Things》 2021年第1期1-9,共9页
A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve.In the train control system,the conversion point of op... A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve.In the train control system,the conversion point of operating mode is the basic of gene encoding and the chromosome composed of multiple genes represents a control scheme,and the initial population can be formed by the way.The fitness function can be designed by the design requirements of the train control stop error,time error and energy consumption.the effectiveness of new individual can be ensured by checking the validity of the original individual when its in the process of selection,crossover and mutation,and the optimal algorithm will be joined all the operators to make the new group not eliminate on the best individual of the last generation.The simulation result shows that the proposed genetic algorithm comparing with the optimized multi-particle simulation model can reduce more than 10%energy consumption,it can provide a large amount of sub-optimal solution and has obvious optimization effect. 展开更多
关键词 Multi-objective improved genetic algorithm urban rail train train operation simulation multi particle optimization model
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Flexible Job Shop Composite Dispatching Rule Mining Approach Based on an Improved Genetic Programming Algorithm
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作者 Xixing Li Qingqing Zhao +4 位作者 Hongtao Tang Xing Guo Mengzhen Zhuang Yibing Li Xi Vincent Wang 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2024年第5期1390-1408,共19页
To obtain a suitable scheduling scheme in an effective time range,the minimum completion time is taken as the objective of Flexible Job Shop scheduling Problems(FJSP)with different scales,and Composite Dispatching Rul... To obtain a suitable scheduling scheme in an effective time range,the minimum completion time is taken as the objective of Flexible Job Shop scheduling Problems(FJSP)with different scales,and Composite Dispatching Rules(CDRs)are applied to generate feasible solutions.Firstly,the binary tree coding method is adopted,and the constructed function set is normalized.Secondly,a CDR mining approach based on an Improved Genetic Programming Algorithm(IGPA)is designed.Two population initialization methods are introduced to enrich the initial population,and a superior and inferior population separation strategy is designed to improve the global search ability of the algorithm.At the same time,two individual mutation methods are introduced to improve the algorithm’s local search ability,to achieve the balance between global search and local search.In addition,the effectiveness of the IGPA and the superiority of CDRs are verified through comparative analysis.Finally,Deep Reinforcement Learning(DRL)is employed to solve the FJSP by incorporating the CDRs as the action set,the selection times are counted to further verify the superiority of CDRs. 展开更多
关键词 flexible job shop scheduling composite dispatching rule improved genetic programming algorithm deep reinforcement learning
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Study on Control Performance of Bearing Temperature based on Genetic Algorithm
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作者 Nianqing Tang 《International Journal of Technology Management》 2015年第1期29-31,共3页
In order to improve the control effect of the bearing, this article studies the temperature control technology to improve the genetic algorithm, at the same time, analyze temperature simulation of bearing based on fuz... In order to improve the control effect of the bearing, this article studies the temperature control technology to improve the genetic algorithm, at the same time, analyze temperature simulation of bearing based on fuzzy PID control technology and improved genetic algorithm, the simulation results show that, the control method has good robustness based on Improved Genetic Algorithm. It can monitor a plurality of beating temperature, provides a new method for the detection and prevention of bearing fault. 展开更多
关键词 Beating' s temperature improved genetic algorithm temperature control
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OPTIMIZATION ON ANTENNA PATTERN OF SPACEBORNE SAR WITH IMPROVED NSGA-Ⅱ 被引量:2
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作者 Xiao Jiang Wang Xiaoqing +1 位作者 Zhu Minhui Xiao Liu 《Journal of Electronics(China)》 2009年第4期443-447,共5页
Optimization of antenna array pattern used in a spaceborne Synthetic Aperture Radar (SAR) system is considered in this study. A robust evolutionary algorithm, Non-dominated Sorting Genetic Algorithms (the improved NS... Optimization of antenna array pattern used in a spaceborne Synthetic Aperture Radar (SAR) system is considered in this study. A robust evolutionary algorithm, Non-dominated Sorting Genetic Algorithms (the improved NSGA-Ⅱ), is applied on a spaceborne SAR antenna pattern design. The system consists of two objective functions with two constraints. Pareto fronts are generated as a result of multi-objective optimization. After being validated by a test problem ZDT4, the algorithms are used to synthesize spaceborne SAR antenna radiation pattern. The good results with low Ambi- guity-to-Signal Ratio (ASR) and high directivity are obtained in the paper. 展开更多
关键词 Synthetic Aperture Radar (SAR) Radiation pattern improved Non-dominated Sorting genetic algorithms (NSGA)-Ⅱ Ambiguity-to-Signal Ratio (ASR)
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考虑交货期的双资源柔性作业车间节能调度 被引量:4
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作者 张洪亮 徐静茹 +1 位作者 谈波 徐公杰 《系统仿真学报》 CAS CSCD 北大核心 2023年第4期734-746,共13页
为解决含有机器和工人双资源约束的柔性作业车间节能调度问题,在考虑交货期的基础上,建立了以总提前和拖期惩罚值及总能耗最小为目标的双资源柔性作业车间节能调度模型。提出了一种改进的非支配排序遗传算法(improved non-dominated sor... 为解决含有机器和工人双资源约束的柔性作业车间节能调度问题,在考虑交货期的基础上,建立了以总提前和拖期惩罚值及总能耗最小为目标的双资源柔性作业车间节能调度模型。提出了一种改进的非支配排序遗传算法(improved non-dominated sorting genetic algorithmⅡ,INSGA-Ⅱ)进行求解。针对所优化的目标,设计了一种三阶段解码方法以获得高质量的可行解;利用动态自适应交叉和变异算子以获得更多优良个体;改进拥挤距离以获得收敛性和分布性更优的种群。将INSGA-Ⅱ与多种多目标优化算法进行对比分析,实验结果表明所提算法可行且有效。 展开更多
关键词 双资源约束 柔性作业车间 提前/拖期惩罚 能耗 INSGA-Ⅱ(improved non-dominated sorting genetic algorithmⅡ)
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Research on Flexible Job Shop Scheduling Optimization Based on Segmented AGV 被引量:2
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作者 Qinhui Liu Nengjian Wang +3 位作者 Jiang Li Tongtong Ma Fapeng Li Zhijie Gao 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第3期2073-2091,共19页
As a typical transportation tool in the intelligent manufacturing system,Automatic Guided Vehicle(AGV)plays an indispensable role in the automatic production process of the workshop.Therefore,integrating AGV resources... As a typical transportation tool in the intelligent manufacturing system,Automatic Guided Vehicle(AGV)plays an indispensable role in the automatic production process of the workshop.Therefore,integrating AGV resources into production scheduling has become a research hotspot.For the scheduling problem of the flexible job shop adopting segmented AGV,a dual-resource scheduling optimization mathematical model of machine tools and AGVs is established by minimizing the maximum completion time as the objective function,and an improved genetic algorithmis designed to solve the problem in this study.The algorithmdesigns a two-layer codingmethod based on process coding and machine tool coding and embeds the task allocation of AGV into the decoding process to realize the real dual resource integrated scheduling.When initializing the population,three strategies are designed to ensure the diversity of the population.In order to improve the local search ability and the quality of the solution of the genetic algorithm,three neighborhood structures are designed for variable neighborhood search.The superiority of the improved genetic algorithmand the influence of the location and number of transfer stations on scheduling results are verified in two cases. 展开更多
关键词 Segmented AGV flexible job shop improved genetic algorithm scheduling optimization
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The improved genetic algorithms for digital image correlation method 被引量:3
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作者 唐晨 刘铭 +2 位作者 闫海青 张桂敏 陈湛青 《Chinese Optics Letters》 SCIE EI CAS CSCD 2004年第10期574-577,共4页
We present a global optimization method, called the genetic algorithms (GAs), for digital image/speckle correlation (DISC). The new algorithms do not involve reasonable initial guess of displacement and deformation gr... We present a global optimization method, called the genetic algorithms (GAs), for digital image/speckle correlation (DISC). The new algorithms do not involve reasonable initial guess of displacement and deformation gradient and the calculation of second-order spatial derivatives of the digital images, which are important challenges in practical implementation of DISC. The performance of a GA depends largely on the selection of the genetic operators. We test various operators and propose optimal operators. The algorithms are then verified using simulated images and experimental speckle images. 展开更多
关键词 GENE ERR The improved genetic algorithms for digital image correlation method RGA BODY DISC
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Layout Design-Based Research on Optimization and Assessment Method for Shipbuilding Workshop
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作者 Yang Liu Mei Meng Shuang Liu 《Journal of Marine Science and Application》 2013年第2期152-162,共11页
The research study proposes to examine a three-dimensional visualization program, emphasizing on improving genetic algorithms through the optimization of a layout design-based standard and discrete shipbuilding worksh... The research study proposes to examine a three-dimensional visualization program, emphasizing on improving genetic algorithms through the optimization of a layout design-based standard and discrete shipbuilding workshop. By utilizing a steel processing workshop as an example, the principle of minimum logistic costs will be implemented to obtain an ideological equipment layout, and a mathematical model. The objectiveness is to minimize the total necessary distance traveled between machines. An improved control operator is implemented to improve the iterative efficiency of the genetic algorithm, and yield relevant parameters. The Computer Aided Tri-Dimensional Interface Application (CATIA) software is applied to establish the manufacturing resource base and parametric model of the steel processing workshop. Based on the results of optimized planar logistics, a visual parametric model of the steel processing workshop is constructed, and qualitative and quantitative adjustments then are applied to the model. The method for evaluating the results of the layout is subsequently established through the utilization of AHP. In order to provide a mode of reference to the optimization and layout of the digitalized production workshop, the optimized discrete production workshop will possess a certain level of practical significance. 展开更多
关键词 visual parametric model steel processing workshop layout optimization design improved genetic algorithm assessment methods optimization algorithm shipbuilding workshop
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Optimal Reactive Power Compensation of Distribution Network to Prevent Reactive Power Reverse
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作者 XING Jie CAO Ruilin +1 位作者 QUAN Zhaolong YUAN Zhiqiang 《Journal of Donghua University(English Edition)》 CAS 2021年第3期199-205,共7页
The capacitive reactive power reversal in the urban distribution grid is increasingly prominent at the period of light load in the last years.In severe cases,it will endanger the security and stability of power grid.T... The capacitive reactive power reversal in the urban distribution grid is increasingly prominent at the period of light load in the last years.In severe cases,it will endanger the security and stability of power grid.This paper presents an optimal reactive power compensation method of distribution network to prevent reactive power reverse.Firstly,an integrated reactive power planning(RPP)model with power factor constraints is established.Capacitors and reactors are considered to be installed in the distribution system at the same time.The objective function is the cost minimization of compensation and real power loss with transformers and lines during the planning period.Nodal power factor limits and reactor capacity constraints are new constraints.Then,power factor sensitivity with respect to reactive power is derived.An improved genetic algorithm by power factor sensitivity is used to solve the model.The optimal locations and sizes of reactors and capacitors can avoid reactive power reversal and power factor exceeding the limit.Finally,the effectiveness of the model and algorithm is proven by a typical high-voltage distribution network. 展开更多
关键词 reactive compensation planning high voltage distribution network power actor improved genetic algorithm
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Knowledge-based detection method for SAR targets
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作者 Fei Gao Achang Ru +1 位作者 Jun Wang Shiyi Mao 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第4期573-579,共7页
When the classical constant false-alarm rate (CFAR) combined with fuzzy C-means (FCM) algorithm is applied to target detection in synthetic aperture radar (SAR) images with complex background, CFAR requires bloc... When the classical constant false-alarm rate (CFAR) combined with fuzzy C-means (FCM) algorithm is applied to target detection in synthetic aperture radar (SAR) images with complex background, CFAR requires block-by-block estimation of clutter models and FCM clustering converges to local optimum. To address these problems, this paper pro-poses a new detection algorithm: knowledge-based combined with improved genetic algorithm-fuzzy C-means (GA-FCM) algorithm. Firstly, the algorithm takes target region's maximum and average intensity, area, length of long axis and long-to-short axis ratio of the external ellipse as factors which influence the target appearing probabil- ity. The knowledge-based detection algorithm can produce preprocess results without the need of estimation of clutter models as CFAR does. Afterward the GA-FCM algorithm is improved to cluster pre-process results. It has advantages of incorporating global optimizing ability of GA and local optimizing ability of FCM, which will further eliminate false alarms and get better results. The effectiveness of the proposed technique is experimentally validated with real SAR images. 展开更多
关键词 synthetic aperture radar (SAR) target detection knowledge-based improved genetic algorithm-fuzzy C-means(GA-FCM) algorithm.
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ATwo-LayerOptimal Scheduling Strategy forRural Microgrids Accounting for Flexible Loads
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作者 Guo Zhao Chi Zhang Qiyuan Ren 《Energy Engineering》 EI 2024年第11期3355-3379,共25页
In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the oper... In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits. 展开更多
关键词 Double carbon flexible loads ruralmicrogrid clean energy consumption two-layer scheduling improved adaptive genetic algorithm
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