Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue...Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue,a surrogate-based MOO algorithm is proposed in this paper where Kriging models are employed to approximate objective functions.An efficient sampling strategy is presented to sequentially capture promising samples in the design region for exact evaluations.Firstly,new sample points are generated by the MOO on surro-gate models.Then,new samples are captured by exploiting each objective function.Furthermore,a weighted sum of the improvement of hypervolume(IHV)and the distance to sampled points is calculated to select the new sample.Compared with two well-known MOO algorithms,the proposed algorithm is vali-dated by benchmark problems.In addition,two broadband MMAs are applied to verify the feasibility and efficiency of the proposed algorithm.展开更多
A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated ...A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model.A two-stage guide multi-objective particle swarm optimization(TSG-MOPSO) algorithm was proposed to solve this optimization problem,which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well.Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice.The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO,and can improve the current manual solutions significantly.The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%,respectively.展开更多
Load of an automatic feed mechanism is composed of the stretching force of feed belt at the entrance to lower flexible guidance and the friction force between feed belt and flexible guidance. A mathematical model for ...Load of an automatic feed mechanism is composed of the stretching force of feed belt at the entrance to lower flexible guidance and the friction force between feed belt and flexible guidance. A mathematical model for computing the load was presented. An optimization problem was formulated to determine the attitude of the flexible guidance based on the principle that the potential energy stored in the system was the minimum at the equilibrium. Then the friction force was obtained according to the attitude of guide leaves and the moving velocity of the feed belt and the friction factor. Consequently, the load of the automatic feed mechanism can be calculated. Finally, an example was given to compute the load when the horizontal and elevating firing angles of the automation were respectively 45° and 30°. The computing result can be a criterion to determine the designing parameters of automat.展开更多
Environmental stress screening (ESS) is a technological process to reduce the costly early field failure of electronic components. This paper builds an optimization model for ESS of electronic components to obtain the...Environmental stress screening (ESS) is a technological process to reduce the costly early field failure of electronic components. This paper builds an optimization model for ESS of electronic components to obtain the optimal ESS duration. The failure phenomena of ESS are modeled by mixed distribution, and optimal ESS duration is defined by maximizing life-cycle cost savings under the condition of meeting reliability requirement.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
This paper establishes a mathematical model of the reliability optimization design for the safe-arming system of an air-faced missile, and presents a solving method for the model. The computational results provide a v...This paper establishes a mathematical model of the reliability optimization design for the safe-arming system of an air-faced missile, and presents a solving method for the model. The computational results provide a valuable reference for the reliability design for the safe-arming system of an air-faced missile.展开更多
In this paper, a new amplitude quantization synthesis method for ultralow sidelobe phased arrays is proposed, which is based on the constrained nonlinear optimization algorithm. By introducing a set of critical constr...In this paper, a new amplitude quantization synthesis method for ultralow sidelobe phased arrays is proposed, which is based on the constrained nonlinear optimization algorithm. By introducing a set of critical constraint conditions into the optimization model, we can directly quantize the amplitude distribution instead of replacing it with a continuous equivalent aperture antenna. The mutual coupling and the element patterns are also considered in the quantization synthesis. Finally, some array simulation results are given to show the effectiveness of the method.展开更多
With the passage of time, it has become important to investigate new methods for updating data to better fit the trends of the grey prediction model. The traditional GM(1,1) usually sets the grey action quantity as ...With the passage of time, it has become important to investigate new methods for updating data to better fit the trends of the grey prediction model. The traditional GM(1,1) usually sets the grey action quantity as a constant. Therefore, it cannot effectively fit the dynamic characteristics of the sequence, which results in the grey model having a low precision. The linear grey action quantity model cannot represent the index change law. This paper presents a grey action quantity model, the exponential optimization grey model(EOGM(1,1)), based on the exponential type of grey action quantity; it is constructed based on the exponential characteristics of the grey prediction model. The model can fully reflect the exponential characteristics of the simulation series with time. The exponential sequence has a higher fitting accuracy. The optimized result is verified using a numerical example for the fluctuating sequence and a case study for the index of the tertiary industry's GDP. The results show that the model improves the precision of the grey forecasting model and reduces the prediction error.展开更多
基金supported by the National Key Research and Development Program(2021YFB3502500).
文摘Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue,a surrogate-based MOO algorithm is proposed in this paper where Kriging models are employed to approximate objective functions.An efficient sampling strategy is presented to sequentially capture promising samples in the design region for exact evaluations.Firstly,new sample points are generated by the MOO on surro-gate models.Then,new samples are captured by exploiting each objective function.Furthermore,a weighted sum of the improvement of hypervolume(IHV)and the distance to sampled points is calculated to select the new sample.Compared with two well-known MOO algorithms,the proposed algorithm is vali-dated by benchmark problems.In addition,two broadband MMAs are applied to verify the feasibility and efficiency of the proposed algorithm.
基金Project(2006AA060201) supported by the National High Technology Research and Development Program of China
文摘A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model.A two-stage guide multi-objective particle swarm optimization(TSG-MOPSO) algorithm was proposed to solve this optimization problem,which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well.Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice.The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO,and can improve the current manual solutions significantly.The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%,respectively.
基金Project supported by the Seventh Research Institute of China State Shipbuilding Corporation
文摘Load of an automatic feed mechanism is composed of the stretching force of feed belt at the entrance to lower flexible guidance and the friction force between feed belt and flexible guidance. A mathematical model for computing the load was presented. An optimization problem was formulated to determine the attitude of the flexible guidance based on the principle that the potential energy stored in the system was the minimum at the equilibrium. Then the friction force was obtained according to the attitude of guide leaves and the moving velocity of the feed belt and the friction factor. Consequently, the load of the automatic feed mechanism can be calculated. Finally, an example was given to compute the load when the horizontal and elevating firing angles of the automation were respectively 45° and 30°. The computing result can be a criterion to determine the designing parameters of automat.
文摘Environmental stress screening (ESS) is a technological process to reduce the costly early field failure of electronic components. This paper builds an optimization model for ESS of electronic components to obtain the optimal ESS duration. The failure phenomena of ESS are modeled by mixed distribution, and optimal ESS duration is defined by maximizing life-cycle cost savings under the condition of meeting reliability requirement.
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.
文摘This paper establishes a mathematical model of the reliability optimization design for the safe-arming system of an air-faced missile, and presents a solving method for the model. The computational results provide a valuable reference for the reliability design for the safe-arming system of an air-faced missile.
文摘In this paper, a new amplitude quantization synthesis method for ultralow sidelobe phased arrays is proposed, which is based on the constrained nonlinear optimization algorithm. By introducing a set of critical constraint conditions into the optimization model, we can directly quantize the amplitude distribution instead of replacing it with a continuous equivalent aperture antenna. The mutual coupling and the element patterns are also considered in the quantization synthesis. Finally, some array simulation results are given to show the effectiveness of the method.
基金supported by the National Key Research and Development Program of China(2016YFC1402000)the National Science Foundation of China(41701593+2 种基金7137109871571157)the National Social Science Fund Major Project(14ZDB151)
文摘With the passage of time, it has become important to investigate new methods for updating data to better fit the trends of the grey prediction model. The traditional GM(1,1) usually sets the grey action quantity as a constant. Therefore, it cannot effectively fit the dynamic characteristics of the sequence, which results in the grey model having a low precision. The linear grey action quantity model cannot represent the index change law. This paper presents a grey action quantity model, the exponential optimization grey model(EOGM(1,1)), based on the exponential type of grey action quantity; it is constructed based on the exponential characteristics of the grey prediction model. The model can fully reflect the exponential characteristics of the simulation series with time. The exponential sequence has a higher fitting accuracy. The optimized result is verified using a numerical example for the fluctuating sequence and a case study for the index of the tertiary industry's GDP. The results show that the model improves the precision of the grey forecasting model and reduces the prediction error.