In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
To obtain the optimal process parameters of stamping forming, finite element analysis and optimization technique were integrated via transforming multi-objective issue into a single-objective issue. A Pareto-based gen...To obtain the optimal process parameters of stamping forming, finite element analysis and optimization technique were integrated via transforming multi-objective issue into a single-objective issue. A Pareto-based genetic algorithm was applied to optimizing the head stamping forming process. In the proposed optimal model, fracture, wrinkle and thickness varying are a function of several factors, such as fillet radius, draw-bead position, blank size and blank-holding force. Hence, it is necessary to investigate the relationship between the objective functions and the variables in order to make objective functions varying minimized simultaneously. Firstly, the central composite experimental(CCD) with four factors and five levels was applied, and the experimental data based on the central composite experimental were acquired. Then, the response surface model(RSM) was set up and the results of the analysis of variance(ANOVA) show that it is reliable to predict the fracture, wrinkle and thickness varying functions by the response surface model. Finally, a Pareto-based genetic algorithm was used to find out a set of Pareto front, which makes fracture, wrinkle and thickness varying minimized integrally. A head stamping case indicates that the present method has higher precision and practicability compared with the "trial and error" procedure.展开更多
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
The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-obj...The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.展开更多
The multi-objective genetic algorithm(MOGA) is proposed to calibrate the non-linear camera model of a space manipulator to improve its locational accuracy. This algorithm can optimize the camera model by dynamic balan...The multi-objective genetic algorithm(MOGA) is proposed to calibrate the non-linear camera model of a space manipulator to improve its locational accuracy. This algorithm can optimize the camera model by dynamic balancing its model weight and multi-parametric distributions to the required accuracy. A novel measuring instrument of space manipulator is designed to orbital simulative motion and locational accuracy test. The camera system of space manipulator, calibrated by MOGA algorithm, is used to locational accuracy test in this measuring instrument. The experimental result shows that the absolute errors are [0.07, 1.75] mm for MOGA calibrating model, [2.88, 5.95] mm for MN method, and [1.19, 4.83] mm for LM method. Besides, the composite errors both of LM method and MN method are approximately seven times higher that of MOGA calibrating model. It is suggested that the MOGA calibrating model is superior both to LM method and MN method.展开更多
This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satell...This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satellites. Hence, the mission planning and scheduling of AEOS is a popular research problem. This research investigates AEOS characteristics and establishes a mission planning model based on the working principle and constraints of AEOS as per analysis. To solve the scheduling issue of AEOS, several improved algorithms are developed. Simulation results suggest that these algorithms are effective.展开更多
This paper presents a new hybrid genetic algorithm for the vertex cover problems in which scan-repair and local improvement techniques are used for local optimization. With the hybrid approach, genetic algorithms are ...This paper presents a new hybrid genetic algorithm for the vertex cover problems in which scan-repair and local improvement techniques are used for local optimization. With the hybrid approach, genetic algorithms are used to perform global exploration in a population, while neighborhood search methods are used to perform local exploitation around the chromosomes. The experimental results indicate that hybrid genetic algorithms can obtain solutions of excellent quality to the problem instances with different sizes. The pure genetic algorithms are outperformed by the neighborhood search heuristics procedures combined with genetic algorithms.展开更多
A novel active steering system with force and displacement coupled control(the novel AFS system) was introduced,which has functions of both the active steering and electric power steering.Based on the model of the nov...A novel active steering system with force and displacement coupled control(the novel AFS system) was introduced,which has functions of both the active steering and electric power steering.Based on the model of the novel AFS system and the vehicle three-degree of freedom system,the concept and quantitative formulas of the novel AFS system steering performance were proposed.The steering road feel and steering portability were set as the optimizing targets with the steering stability and steering portability as the constraint conditions.According to the features of constrained optimization of multi-variable function,a multi-variable genetic algorithm for the system parameter optimization was designed.The simulation results show that based on parametric optimization of the multi-objective genetic algorithm,the novel AFS system can improve the steering road feel,steering portability and steering stability,thus the optimization method can provide a theoretical basis for the design and optimization of the novel AFS system.展开更多
This paper presents the design optimization of composite submersible cylindrical pressure hull subjected to 3 MPa hydrostatic pressure.The design optimization study is conducted for cross-ply layups[0_(s)/90_(t)/0_(u)...This paper presents the design optimization of composite submersible cylindrical pressure hull subjected to 3 MPa hydrostatic pressure.The design optimization study is conducted for cross-ply layups[0_(s)/90_(t)/0_(u)],[0_(s)/90_(t)/0_(u)]s,[0_(s)/90_(t)]s and[90_(s)/0_(t)]s considering three uni-directional composites,i.e.Carbon/Epoxy,Glass/Epoxy,and Boron/Epoxy.The optimization study is performed by coupling a Multi-Objective Genetic Algorithm(MOGA)and Analytical Analysis.Minimizing the buoyancy factor and maximizing the buckling load factor are considered as the objectives of the optimization study.The objectives of the optimization are achieved under constraints on the Tsai-Wu,Tsai-Hill and Maximum Stress composite failure criteria and on buckling load factor.To verify the optimization approach,optimization of one particular layup configuration is also conducted in ANSYS with the same objectives and constraints.展开更多
To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description ab...To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.展开更多
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a...This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.展开更多
Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a ki...Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a kind of multi-objective optimization problem.Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors,this work applies an improved non-dominated sorting genetic algorithm Ⅱ(NSGA Ⅱ) to solve it directly by means of optimizing multi-objective functions simultaneously.In the improved NSGA Ⅱ,the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population,the penalty function was used in handling constraints,and the optimal solution was selected according to the method of fuzzy set theory.Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA Ⅱ can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability,and provide a new train of thoughts to design homing trajectory of parafoil system.展开更多
To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solve...To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solved.In this work,a radial-basis function(RBF)neural network was used to mine the potential changes of a greenhouse environment,a temperature error model was established,a multi-objective optimization function of energy consumption was constructed and the corresponding decision parameters were optimized by using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-Ⅱ).The simulation results showed that RBF could clarify the nonlinear relationship among the greenhouse environment variables and decision parameters and the greenhouse temperature.The NSGA-Ⅱ could well search for the Pareto solution for the objective functions.The experimental results showed that after 40 min of combined control of sunshades and sprays,the temperature was reduced from 31℃to 25℃,and the power consumption was 0.5 MJ.Compared with tire three days of July 24,July 25 and July 26,2017,the energy consumption of the controlled production greenhouse was reduced by 37.5%,9.1%and 28.5%,respectively.展开更多
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
基金Project(2012ZX04010-081) supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China
文摘To obtain the optimal process parameters of stamping forming, finite element analysis and optimization technique were integrated via transforming multi-objective issue into a single-objective issue. A Pareto-based genetic algorithm was applied to optimizing the head stamping forming process. In the proposed optimal model, fracture, wrinkle and thickness varying are a function of several factors, such as fillet radius, draw-bead position, blank size and blank-holding force. Hence, it is necessary to investigate the relationship between the objective functions and the variables in order to make objective functions varying minimized simultaneously. Firstly, the central composite experimental(CCD) with four factors and five levels was applied, and the experimental data based on the central composite experimental were acquired. Then, the response surface model(RSM) was set up and the results of the analysis of variance(ANOVA) show that it is reliable to predict the fracture, wrinkle and thickness varying functions by the response surface model. Finally, a Pareto-based genetic algorithm was used to find out a set of Pareto front, which makes fracture, wrinkle and thickness varying minimized integrally. A head stamping case indicates that the present method has higher precision and practicability compared with the "trial and error" procedure.
文摘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.
基金Projects(51005115, 51005248) supported by the National Natural Science Foundation of ChinaProject(SKLMT-KFKT-201105)supported by the Visiting Scholar Foundation of State Key Laboratory of Mechanical Transmission in Chongqing University, ChinaProject(QC201101) supported by Visiting Scholar Foundation of the Automobile Engineering Key Laboratory of Jiangsu Province, China
文摘The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.
基金Project(J132012C001)supported by Technological Foundation of ChinaProject(2011YQ04013606)supported by National Major Scientific Instrument & Equipment Developing Projects,China
文摘The multi-objective genetic algorithm(MOGA) is proposed to calibrate the non-linear camera model of a space manipulator to improve its locational accuracy. This algorithm can optimize the camera model by dynamic balancing its model weight and multi-parametric distributions to the required accuracy. A novel measuring instrument of space manipulator is designed to orbital simulative motion and locational accuracy test. The camera system of space manipulator, calibrated by MOGA algorithm, is used to locational accuracy test in this measuring instrument. The experimental result shows that the absolute errors are [0.07, 1.75] mm for MOGA calibrating model, [2.88, 5.95] mm for MN method, and [1.19, 4.83] mm for LM method. Besides, the composite errors both of LM method and MN method are approximately seven times higher that of MOGA calibrating model. It is suggested that the MOGA calibrating model is superior both to LM method and MN method.
基金supported by the National Natural Science Foundation of China(7127106671171065+1 种基金71202168)the Natural Science Foundation of Heilongjiang Province(GC13D506)
文摘This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satellites. Hence, the mission planning and scheduling of AEOS is a popular research problem. This research investigates AEOS characteristics and establishes a mission planning model based on the working principle and constraints of AEOS as per analysis. To solve the scheduling issue of AEOS, several improved algorithms are developed. Simulation results suggest that these algorithms are effective.
基金This project was supported by the National Natural Science Foundation of China the Open Project Foundation of Comput-er Software New Technique National Key Laboratory of Nanjing University.
文摘This paper presents a new hybrid genetic algorithm for the vertex cover problems in which scan-repair and local improvement techniques are used for local optimization. With the hybrid approach, genetic algorithms are used to perform global exploration in a population, while neighborhood search methods are used to perform local exploitation around the chromosomes. The experimental results indicate that hybrid genetic algorithms can obtain solutions of excellent quality to the problem instances with different sizes. The pure genetic algorithms are outperformed by the neighborhood search heuristics procedures combined with genetic algorithms.
基金Project(51005115) supported by the National Natural Science Foundation of ChinaProject(KF11201) supported by the Science Fund of State Key Laboratory of Automotive Safety and Energy,ChinaProject(201105) supported by the Visiting Scholar Foundation of the State Key Laboratory of Mechanical Transmission in Chongqing University,China
文摘A novel active steering system with force and displacement coupled control(the novel AFS system) was introduced,which has functions of both the active steering and electric power steering.Based on the model of the novel AFS system and the vehicle three-degree of freedom system,the concept and quantitative formulas of the novel AFS system steering performance were proposed.The steering road feel and steering portability were set as the optimizing targets with the steering stability and steering portability as the constraint conditions.According to the features of constrained optimization of multi-variable function,a multi-variable genetic algorithm for the system parameter optimization was designed.The simulation results show that based on parametric optimization of the multi-objective genetic algorithm,the novel AFS system can improve the steering road feel,steering portability and steering stability,thus the optimization method can provide a theoretical basis for the design and optimization of the novel AFS system.
基金This work is supported by the National Natural Science Foundation of China research grant“Study on the characteristic motion and load of bubbles near a solid boundary in shear flows”(51679056)Natural Science Foundation of Heilongjiang Province of China(E2016024).
文摘This paper presents the design optimization of composite submersible cylindrical pressure hull subjected to 3 MPa hydrostatic pressure.The design optimization study is conducted for cross-ply layups[0_(s)/90_(t)/0_(u)],[0_(s)/90_(t)/0_(u)]s,[0_(s)/90_(t)]s and[90_(s)/0_(t)]s considering three uni-directional composites,i.e.Carbon/Epoxy,Glass/Epoxy,and Boron/Epoxy.The optimization study is performed by coupling a Multi-Objective Genetic Algorithm(MOGA)and Analytical Analysis.Minimizing the buoyancy factor and maximizing the buckling load factor are considered as the objectives of the optimization study.The objectives of the optimization are achieved under constraints on the Tsai-Wu,Tsai-Hill and Maximum Stress composite failure criteria and on buckling load factor.To verify the optimization approach,optimization of one particular layup configuration is also conducted in ANSYS with the same objectives and constraints.
文摘To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.
文摘This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.
基金Project(61273138)supported by the National Natural Science Foundation of ChinaProject(14JCZDJC39300)supported by the Key Fund of Tianjin,China
文摘Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a kind of multi-objective optimization problem.Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors,this work applies an improved non-dominated sorting genetic algorithm Ⅱ(NSGA Ⅱ) to solve it directly by means of optimizing multi-objective functions simultaneously.In the improved NSGA Ⅱ,the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population,the penalty function was used in handling constraints,and the optimal solution was selected according to the method of fuzzy set theory.Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA Ⅱ can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability,and provide a new train of thoughts to design homing trajectory of parafoil system.
基金Supported by the National"Thirteenth Five-year Plan"National Key Program(2016YFD0701301)the Heilongjiang Provincial Achievement Transformation Fund Project(NB08B-011)。
文摘To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solved.In this work,a radial-basis function(RBF)neural network was used to mine the potential changes of a greenhouse environment,a temperature error model was established,a multi-objective optimization function of energy consumption was constructed and the corresponding decision parameters were optimized by using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-Ⅱ).The simulation results showed that RBF could clarify the nonlinear relationship among the greenhouse environment variables and decision parameters and the greenhouse temperature.The NSGA-Ⅱ could well search for the Pareto solution for the objective functions.The experimental results showed that after 40 min of combined control of sunshades and sprays,the temperature was reduced from 31℃to 25℃,and the power consumption was 0.5 MJ.Compared with tire three days of July 24,July 25 and July 26,2017,the energy consumption of the controlled production greenhouse was reduced by 37.5%,9.1%and 28.5%,respectively.
