Conventional pit excavation engineering methods often struggle to manage the complex deformation patterns associated with asymmetric excavations,resulting in significant safety risks and increased project costs.These ...Conventional pit excavation engineering methods often struggle to manage the complex deformation patterns associated with asymmetric excavations,resulting in significant safety risks and increased project costs.These challenges highlight the need for more precise and efficient design methodologies to ensure structural stability and economic feasibility.This research proposes an innovative automatic optimization inverse design method(AOIDM)that integrates an enhanced genetic algorithm(EGA)with a multiobjective optimization model.By combining advanced computational techniques with engineering principles,this approach improves search efficiency by 30%and enhances deformation control accuracy by 25%.Additionally,the approach exhibits potential for reducing carbon emissions to align with sustainable engineering goals.The effectiveness of this approach was validated through comprehensive data analysis and practical case studies,demonstrating its ability to optimize retaining structure designs under complex asymmetric loading conditions.This research establishes a new standard for precision and efficiency in automated excavation design,with accompanying improvements in safety and cost-effectiveness.Furthermore,it lays the foundation for future geotechnical engineering advancements,offering a robust solution to one of the most challenging aspects of modern excavation projects.展开更多
With the recent boom in unmanned aerial vehicle (UAV) technology, many UAV applications involving complex and risky tasks in military and civilian fields have emerged, such as military strikes and disaster monitoring....With the recent boom in unmanned aerial vehicle (UAV) technology, many UAV applications involving complex and risky tasks in military and civilian fields have emerged, such as military strikes and disaster monitoring. Task allocation for UAVs is the process of planning the division of work among UAVs, controlled from ground stations by human operators. This study formulates the UAV task-allocation problem as an extended traveling salesman problem and presents a novel UAV task-allocation model for complex air concentration monitoring tasks. Then, an optimized non-dominated sorting genetic algorithm III (NSGA-III) based on a twin-exclusion mechanism, hierarchical objective-domination operator, and segmented gene encoding (i.e., NSGA-III-TEHOD) is developed to solve complex task-allocation problems involving multiple UAVs, hierarchical objectives, obstacles, and ambient wind. The algorithm is tested in several simulations, and the results demonstrate that the new algorithm outperforms NSGA-III, non-dominated sorting genetic algorithm II (NSGA-II), and genetic algorithm (GA) in terms of efficiency of global convergence and early maturation prevention and is available for the hierarchical objective-optimization problems.展开更多
This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathe...This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results.The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs).Successful finding of optimal ways to drive these processes were reported.Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.展开更多
In this article, a multiobjective optimization strategy for an industrial naphtha continuous catalytic reform-ing process that aims to obtain aromatic products is proposed. The process model is based on a 20-lumped ki...In this article, a multiobjective optimization strategy for an industrial naphtha continuous catalytic reform-ing process that aims to obtain aromatic products is proposed. The process model is based on a 20-lumped kinetics re-action network and has been proved to be quite effective in terms of industrial application. The primary objectives in-clude maximization of yield of the aromatics and minimization of the yield of heavy aromatics. Four reactor inlet tem-peratures, reaction pressure, and hydrogen-to-oil molar ratio are selected as the decision variables. A genetic algorithm, which is proposed by the authors and named as the neighborhood and archived genetic algorithm (NAGA), is applied to solve this multiobjective optimization problem. The relations between each decision variable and the two objectives are also proposed and used for choosing a suitable solution from the obtained Pareto set.展开更多
In industrial amine plants the optimized operating conditions are obtained from the conclusion of occurred events and challenges that are normal in the working units. For the sake of reducing the costs, time consuming...In industrial amine plants the optimized operating conditions are obtained from the conclusion of occurred events and challenges that are normal in the working units. For the sake of reducing the costs, time consuming, and preventing unsuitable accidents, the optimization could be performed by a computer program. In this paper, simulation and parameter analysis of amine plant is performed at first. The optimization of this unit is studied using Non-Dominated Sorting Genetic Algorithm-II in order to produce sweet gas with CO 2 mole percentage less than 2.0% and H 2 S concentration less than 10 ppm for application in Fischer-Tropsch synthesis. The simulation of the plant in HYSYS v.3.1 software has been linked with MATLAB code for real-parameter NSGA-II to simulate and optimize the amine process. Three scenarios are selected to cover the effect of （DEA/MDEA） mass composition percent ratio at amine solution on objective functions. Results show that sour gas temperature and pressure of 33.98 ？ C and 14.96 bar, DEA/CO 2 molar flow ratio of 12.58, regeneration gas temperature and pressure of 94.92 ？ C and 3.0 bar, regenerator pressure of 1.53 bar, and ratio of DEA/MDEA = 20%/10% are the best values for minimizing plant energy consumption, amine circulation rate, and carbon dioxide recovery.展开更多
Rankine source method,optimization technology,parametric modeling technology,and improved multiobjective optimization algorithm were combined to investigate the multiobjective optimization design of hull form.A multio...Rankine source method,optimization technology,parametric modeling technology,and improved multiobjective optimization algorithm were combined to investigate the multiobjective optimization design of hull form.A multiobjective and multilevel optimization design framework was constructed for the comprehensive navigation performance of ships.CAESES software was utilized as the optimization platform,and nondominated sorting genetic algorithm II(NSGA-II)was used to conduct multiobjective optimization research on the resistance and sea-keeping performance of the ITTC Ship A-2 fishing vessel.Optimization objectives of this study are heave/pitch response amplitude and wave-making resistance.Taking the displacement and the length between perpendiculars as constraints,we optimized the profile of the hull.Analytic hierarchy process(AHP)and technique for order preference by similarity to ideal solution(TOPSIS)were used to sort and select Pareto solutions and determine weight coefficient of each navigation performance objective in the general objective.Finally,the hydrodynamic performance before and after the parametric deformation of the hull was compared.The results show that both the wave-making resistance and heave/pitch amplitude of the optimized hull form are reduced,and the satisfactory optimal hull form is obtained.The results of this study have a certain reference value for the initial stage of multiobjective optimization design of hull form.展开更多
This paper developed a new method that adaptively adjusts a design space by considering the actual solution distribution of a problem to overcome the conventional design-space adaptation method that assumes the soluti...This paper developed a new method that adaptively adjusts a design space by considering the actual solution distribution of a problem to overcome the conventional design-space adaptation method that assumes the solutions distribution to be a normal distribution because the distributions of solutions are rarely normal distributions for real-world problems.The developed method was applied to nineteen multiobjective test functions that are widely used to evaluate the characteristics and performance of optimization approaches.The results showed that this method adapted the design space to an appropriate design space where the solution existence probability was high.The optimization performance achieved using the developed method was higher than that of the conventional methods.Furthermore,the developed method was applied to the conceptual design of an unmanned spacecraft to confirm its validity in real-world design and multidisciplinaryoptimization problems.The results showed that the Pareto solutions of the developed method were superior to those of conventional methods.Additionally,the optimization efficiency with the developed method was improved by more than 1.4 times over that of the conventional methods.In this regard,the developed method has the potential to be applied to complicated real-world optimization problems to achieve better performance and efficiency.展开更多
To meet the demands of advanced electronic devices,inorganic glasses are required to have comprehensive dielectric,thermal,and mechanical properties.However,the complex composition–property relationship and vast comp...To meet the demands of advanced electronic devices,inorganic glasses are required to have comprehensive dielectric,thermal,and mechanical properties.However,the complex composition–property relationship and vast compositional diversity hinder optimization.This study developed machine learning models to predict permittivity,dielectric loss,thermal conductivity,coefficient of thermal expansion,and Young’s modulus based on the composition features of inorganic glasses.The optimal models achieve R^(2)values of 0.9614,0.7411,0.9454,0.9684,and 0.8164,respectively.By integrating domain knowledge with model-agnostic interpretation methods,feature contributions and interactions were analyzed.The mixed alkali effect is crucial for property regulation,especially Na-K for dielectric loss and Na-Li for thermal conductivity.Boron anomaly shifts the high-λregion to a balanced composition of alkali metals with rising B%.The multiobjective optimization of properties was realized using a genetic algorithm framework.After 23 iterations,the optimal material in the MgO-Al_(2)O_(3)-B_(2)O_(3)-SiO2 system exhibitsε_(r)=4.78,tanδ=0.00063,λ=2.59 W/(m⋅K),α=50.27�10−7K−1,and E=82.41 GPa,outperforming all materials in the dataset.The computational effort was reduced to 1/19 of that required using exhaustive search methods.This study provides a model interpretation framework and an effective multiobjective optimization strategy for glass design.展开更多
The optional types of power source and actuator in the aircraft are more and more diverse due to fast development in more electric technology, which makes the combinations of different power sources and actuators beco...The optional types of power source and actuator in the aircraft are more and more diverse due to fast development in more electric technology, which makes the combinations of different power sources and actuators become extremely complex in the architecture optimization process of airborne actuation system. The traditional ＂trial and error＂ method cannot satisfy the design demands. In this paper, firstly, the composition of more electric aircraft （MEA） flight control actuation system （FCAS） is introduced, and the possible architecture quantity is calculated. Secondly, the evaluation criteria of FCAS architecture with respect to safe reliability, weight and efficiency are proposed, and the evaluation criteria values are calculated in the case that each control surface adopts the same actuator configuration. Finally, the optimization results of MEA FCAS architecture are obtained by applying genetic algorithm （GA）. Compared to the traditional actuation system architecture, which only adopts servo valve controlled hydraulic actuators, the weight of the optimized more electric actuation system architecture can be reduced by 6%, and the efficiency can be improved by 30% based on the safe reliability requirements.展开更多
A quality of service （QoS） or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path （MC...A quality of service （QoS） or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path （MCP） problem, and has been proven to be NP-complete that cannot be exactly solved in a polynomial time. The NPC problem is converted into a multiobjective optimization problem with constraints to be solved with a genetic algorithm. Based on the Pareto optimum, a constrained routing computation method is proposed to generate a set of nondominated optimal routes with the genetic algorithm mechanism. The convergence and time complexity of the novel algorithm is analyzed. Experimental results show that multiobjective evolution is highly responsive and competent for the Pareto optimum-based route selection. When this method is applied to a MPLS and metropolitan-area network, it will be capable of optimizing the transmission performance.展开更多
Law level of RRO(Repeatable Run Out),NRRO(Non Repe at able Run Out),and lightweight construction are a major trend in the high-speed HDD(Hard Disk Drive)sytem to reduce track misregestration and to achieve high track ...Law level of RRO(Repeatable Run Out),NRRO(Non Repe at able Run Out),and lightweight construction are a major trend in the high-speed HDD(Hard Disk Drive)sytem to reduce track misregestration and to achieve high track density,which lead to succeed in the market.However,it is not easy to r educe RRO,NRRO,and the weight of the spinning disk spindle system efficiently because lightweight construction and or bearing stiffness changes often yields a decrease in the static and dynamic stiffness of the system,and consequently hi gh vibrations may be generated as a results.Therefore,it is of importance to e valuate in advance the accurate dynamic behavior of the high speed spinning disk spindle system of a HDD sysem.This study introduces an optimum design of the high speed spinning disk spindle system of a HDD for minimum RRO,NRRO,and lightweight construction using a gene tic algorithm.The spinning disk,hub,and bearing components of a HDD system ar e modelled as appropriate finite elements respectively and their equations of mo tion are derived to construct the system equations of the whole spinning disk sp indle system of the HDD system.The RRO and NRRO responses of the spinning disk,due to exciting forces arised from ball bearing faults and rotating unbalance,are analyzed.In the design optimation,the hub thickness,the disk thickness,bearing positio ns(or bearing span)and bearing stiffness were set as design variables.The uni que objective function is obtained by multiplying an appropriate weighting facto r by multi-objective functions,such as RRO,NRRO,and the total weight of HDD the system.The constraints are maximum RRO limit,maximum weight linit,and the critical speed limit of the HDD spindle system.Results show that the RRO,NRRO,and weight are reduced by 6%,66.7%and 28%r espectively compared with the initial design of the HDD system.Therefore,thi s present study can be used for an optimum design of the spinning disk spindle s ystem of a HDD for lightweight construction and low vibrations.展开更多
Aerodynamic optimization design of compressor blade shape is a design challenge at present because itis inherently a multiobjective problem. Thus, multiobjective Genetic Algorithms based on the multibranch simulated a...Aerodynamic optimization design of compressor blade shape is a design challenge at present because itis inherently a multiobjective problem. Thus, multiobjective Genetic Algorithms based on the multibranch simulated annealing selection and collection of Pareto solutions strategy have been developedand applied to the optimum design of compressor cascade. The present multiobjective design seeks highpressure rise, high flow turning angle and low total pressure loss at a low inlet Mach number. Paretosolutions obtain the better aerodynamic performance of the cascade than the existing Control DiffusionAirfoil. From the Pareto solutions, the decision maker would be able to find a design that satisfies hisdesign goal best. The results indicate that the feasibility of multiobjective Genetic Algorithms as amultiple objectives optimization tool in the engineering field.展开更多
Hydraulic circuits with high speed on/off valve(HSV)for servo control have become commonplace in aerospace.However,the individual valve that is not volume-optimized results in a large total size of hydraulic control s...Hydraulic circuits with high speed on/off valve(HSV)for servo control have become commonplace in aerospace.However,the individual valve that is not volume-optimized results in a large total size of hydraulic control system,diminishing the practicality.To address this issue,the high-precision equivalent reluctance model of the HSV is established by employing an equivalent magnetic circuit,on which the dynamic characteristic of the HSV,as well as the effects of structural parameters on switching behaviour,are investigated.Based on this model,multi-objective optimization is adopted to design an HSV with faster dynamic performance and smaller volume,NSGA-II genetic algorithm is applied to obtain the Pareto front of the desired objectives.To assess the impact before and after optimization,an HSV based on the optimized structure is manufactured and tested.The experimental results show that the optimized HSV reduces 47.1%of its solenoid volume while improving opening and closing dynamic performance by 14.8%and 43.0%respectively,increasing maximum switching frequency by 6.2%,and expanding flow linear control area by 6.7%.These results validate the optimized structure and indicate that the optimization method provided in the paper is beneficial for developing superior HSV.展开更多
In this paper we present a new optimization algorithm, and the proposed algorithm operates in two phases. In the first one, multiobjective version of genetic algorithm is used as search engine in order to generate app...In this paper we present a new optimization algorithm, and the proposed algorithm operates in two phases. In the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm is based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept e-dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems.展开更多
传统滚齿工装设计依赖经验积累和试错法,缺乏系统的分析手段,导致设计周期长、成本高。针对这一问题,本研究针对某盘类齿轮,利用有限元(finite element analysis, FEA)工具,开发出一套滚齿快换工装,从而提高滚齿工装的整体设计水平和力...传统滚齿工装设计依赖经验积累和试错法,缺乏系统的分析手段,导致设计周期长、成本高。针对这一问题,本研究针对某盘类齿轮,利用有限元(finite element analysis, FEA)工具,开发出一套滚齿快换工装,从而提高滚齿工装的整体设计水平和力学性能。首先基于圆柱渐开线斜齿轮滚齿加工原理完成工装结构设计,然后运用ANSYS Workbench软件进行仿真分析,分析结果表明工装的结构强度满足加工要求,但胀套上的等效应力值超出许用应力24%。为改善胀套的等效应力分布并提升其使用性能,采用基于遗传算法的多目标优化方法对其进行优化设计,优化后胀套在变形量与等效应力满足要求的前提下,其疲劳寿命由594.7次循环提升至6 666.3次循环。展开更多
基金supported by the National Key R&D Program of China(Grant No.2023YFC3009400)the National Natural Science Foundation of China(Grant Nos.52238009 and 52208344).
文摘Conventional pit excavation engineering methods often struggle to manage the complex deformation patterns associated with asymmetric excavations,resulting in significant safety risks and increased project costs.These challenges highlight the need for more precise and efficient design methodologies to ensure structural stability and economic feasibility.This research proposes an innovative automatic optimization inverse design method(AOIDM)that integrates an enhanced genetic algorithm(EGA)with a multiobjective optimization model.By combining advanced computational techniques with engineering principles,this approach improves search efficiency by 30%and enhances deformation control accuracy by 25%.Additionally,the approach exhibits potential for reducing carbon emissions to align with sustainable engineering goals.The effectiveness of this approach was validated through comprehensive data analysis and practical case studies,demonstrating its ability to optimize retaining structure designs under complex asymmetric loading conditions.This research establishes a new standard for precision and efficiency in automated excavation design,with accompanying improvements in safety and cost-effectiveness.Furthermore,it lays the foundation for future geotechnical engineering advancements,offering a robust solution to one of the most challenging aspects of modern excavation projects.
基金the National Key Research and Development Program of China (No. 2017YFC0209902)。
文摘With the recent boom in unmanned aerial vehicle (UAV) technology, many UAV applications involving complex and risky tasks in military and civilian fields have emerged, such as military strikes and disaster monitoring. Task allocation for UAVs is the process of planning the division of work among UAVs, controlled from ground stations by human operators. This study formulates the UAV task-allocation problem as an extended traveling salesman problem and presents a novel UAV task-allocation model for complex air concentration monitoring tasks. Then, an optimized non-dominated sorting genetic algorithm III (NSGA-III) based on a twin-exclusion mechanism, hierarchical objective-domination operator, and segmented gene encoding (i.e., NSGA-III-TEHOD) is developed to solve complex task-allocation problems involving multiple UAVs, hierarchical objectives, obstacles, and ambient wind. The algorithm is tested in several simulations, and the results demonstrate that the new algorithm outperforms NSGA-III, non-dominated sorting genetic algorithm II (NSGA-II), and genetic algorithm (GA) in terms of efficiency of global convergence and early maturation prevention and is available for the hierarchical objective-optimization problems.
文摘This paper describes empirical research on the model, optimization and supervisory control of beer fermentation.Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results.The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs).Successful finding of optimal ways to drive these processes were reported.Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.
基金Supported by the National Natural Science Foundation of China (No.60421002).
文摘In this article, a multiobjective optimization strategy for an industrial naphtha continuous catalytic reform-ing process that aims to obtain aromatic products is proposed. The process model is based on a 20-lumped kinetics re-action network and has been proved to be quite effective in terms of industrial application. The primary objectives in-clude maximization of yield of the aromatics and minimization of the yield of heavy aromatics. Four reactor inlet tem-peratures, reaction pressure, and hydrogen-to-oil molar ratio are selected as the decision variables. A genetic algorithm, which is proposed by the authors and named as the neighborhood and archived genetic algorithm (NAGA), is applied to solve this multiobjective optimization problem. The relations between each decision variable and the two objectives are also proposed and used for choosing a suitable solution from the obtained Pareto set.
文摘In industrial amine plants the optimized operating conditions are obtained from the conclusion of occurred events and challenges that are normal in the working units. For the sake of reducing the costs, time consuming, and preventing unsuitable accidents, the optimization could be performed by a computer program. In this paper, simulation and parameter analysis of amine plant is performed at first. The optimization of this unit is studied using Non-Dominated Sorting Genetic Algorithm-II in order to produce sweet gas with CO 2 mole percentage less than 2.0% and H 2 S concentration less than 10 ppm for application in Fischer-Tropsch synthesis. The simulation of the plant in HYSYS v.3.1 software has been linked with MATLAB code for real-parameter NSGA-II to simulate and optimize the amine process. Three scenarios are selected to cover the effect of （DEA/MDEA） mass composition percent ratio at amine solution on objective functions. Results show that sour gas temperature and pressure of 33.98 ？ C and 14.96 bar, DEA/CO 2 molar flow ratio of 12.58, regeneration gas temperature and pressure of 94.92 ？ C and 3.0 bar, regenerator pressure of 1.53 bar, and ratio of DEA/MDEA = 20%/10% are the best values for minimizing plant energy consumption, amine circulation rate, and carbon dioxide recovery.
基金the National Natural Science Foundation of China(Nos.51779135 and 51009087)the Natural Science Foundation of Shanghai(No.14ZR1419500)。
文摘Rankine source method,optimization technology,parametric modeling technology,and improved multiobjective optimization algorithm were combined to investigate the multiobjective optimization design of hull form.A multiobjective and multilevel optimization design framework was constructed for the comprehensive navigation performance of ships.CAESES software was utilized as the optimization platform,and nondominated sorting genetic algorithm II(NSGA-II)was used to conduct multiobjective optimization research on the resistance and sea-keeping performance of the ITTC Ship A-2 fishing vessel.Optimization objectives of this study are heave/pitch response amplitude and wave-making resistance.Taking the displacement and the length between perpendiculars as constraints,we optimized the profile of the hull.Analytic hierarchy process(AHP)and technique for order preference by similarity to ideal solution(TOPSIS)were used to sort and select Pareto solutions and determine weight coefficient of each navigation performance objective in the general objective.Finally,the hydrodynamic performance before and after the parametric deformation of the hull was compared.The results show that both the wave-making resistance and heave/pitch amplitude of the optimized hull form are reduced,and the satisfactory optimal hull form is obtained.The results of this study have a certain reference value for the initial stage of multiobjective optimization design of hull form.
基金co-supported by the National Research Foundation of Korea(No.NRF-2021R1A2C2013363)grant funded by the Korea government(Ministry of Science and ICT,MSIT)the Convergence Security Core Talent Training Business Support Program(No.IITP-2023-RS-2023-00266615)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation)funded by the MSIT(Ministry of Science and ICT),Korea.
文摘This paper developed a new method that adaptively adjusts a design space by considering the actual solution distribution of a problem to overcome the conventional design-space adaptation method that assumes the solutions distribution to be a normal distribution because the distributions of solutions are rarely normal distributions for real-world problems.The developed method was applied to nineteen multiobjective test functions that are widely used to evaluate the characteristics and performance of optimization approaches.The results showed that this method adapted the design space to an appropriate design space where the solution existence probability was high.The optimization performance achieved using the developed method was higher than that of the conventional methods.Furthermore,the developed method was applied to the conceptual design of an unmanned spacecraft to confirm its validity in real-world design and multidisciplinaryoptimization problems.The results showed that the Pareto solutions of the developed method were superior to those of conventional methods.Additionally,the optimization efficiency with the developed method was improved by more than 1.4 times over that of the conventional methods.In this regard,the developed method has the potential to be applied to complicated real-world optimization problems to achieve better performance and efficiency.
基金supported by the Joint Funds of the National Natural Science Foundation of China(No.U24A2052)the Program of Shanghai Academic Research Leader(No.23XD1404600)+1 种基金the Postdoctoral Fellowship Program of the China Postdoctoral Science Foundation(No.GZC20232825)the Shanghai Eastern Talent Plan(No.QNKJ2024026).
文摘To meet the demands of advanced electronic devices,inorganic glasses are required to have comprehensive dielectric,thermal,and mechanical properties.However,the complex composition–property relationship and vast compositional diversity hinder optimization.This study developed machine learning models to predict permittivity,dielectric loss,thermal conductivity,coefficient of thermal expansion,and Young’s modulus based on the composition features of inorganic glasses.The optimal models achieve R^(2)values of 0.9614,0.7411,0.9454,0.9684,and 0.8164,respectively.By integrating domain knowledge with model-agnostic interpretation methods,feature contributions and interactions were analyzed.The mixed alkali effect is crucial for property regulation,especially Na-K for dielectric loss and Na-Li for thermal conductivity.Boron anomaly shifts the high-λregion to a balanced composition of alkali metals with rising B%.The multiobjective optimization of properties was realized using a genetic algorithm framework.After 23 iterations,the optimal material in the MgO-Al_(2)O_(3)-B_(2)O_(3)-SiO2 system exhibitsε_(r)=4.78,tanδ=0.00063,λ=2.59 W/(m⋅K),α=50.27�10−7K−1,and E=82.41 GPa,outperforming all materials in the dataset.The computational effort was reduced to 1/19 of that required using exhaustive search methods.This study provides a model interpretation framework and an effective multiobjective optimization strategy for glass design.
基金National Natural Science Foundation of China （50675009） International Science ＆ Technology Cooperation Program of China （2010DFA72540）
文摘The optional types of power source and actuator in the aircraft are more and more diverse due to fast development in more electric technology, which makes the combinations of different power sources and actuators become extremely complex in the architecture optimization process of airborne actuation system. The traditional ＂trial and error＂ method cannot satisfy the design demands. In this paper, firstly, the composition of more electric aircraft （MEA） flight control actuation system （FCAS） is introduced, and the possible architecture quantity is calculated. Secondly, the evaluation criteria of FCAS architecture with respect to safe reliability, weight and efficiency are proposed, and the evaluation criteria values are calculated in the case that each control surface adopts the same actuator configuration. Finally, the optimization results of MEA FCAS architecture are obtained by applying genetic algorithm （GA）. Compared to the traditional actuation system architecture, which only adopts servo valve controlled hydraulic actuators, the weight of the optimized more electric actuation system architecture can be reduced by 6%, and the efficiency can be improved by 30% based on the safe reliability requirements.
基金the Natural Science Foundation of Anhui Province of China (050420212)the Excellent Youth Science and Technology Foundation of Anhui Province of China (04042069).
文摘A quality of service （QoS） or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path （MCP） problem, and has been proven to be NP-complete that cannot be exactly solved in a polynomial time. The NPC problem is converted into a multiobjective optimization problem with constraints to be solved with a genetic algorithm. Based on the Pareto optimum, a constrained routing computation method is proposed to generate a set of nondominated optimal routes with the genetic algorithm mechanism. The convergence and time complexity of the novel algorithm is analyzed. Experimental results show that multiobjective evolution is highly responsive and competent for the Pareto optimum-based route selection. When this method is applied to a MPLS and metropolitan-area network, it will be capable of optimizing the transmission performance.
文摘Law level of RRO(Repeatable Run Out),NRRO(Non Repe at able Run Out),and lightweight construction are a major trend in the high-speed HDD(Hard Disk Drive)sytem to reduce track misregestration and to achieve high track density,which lead to succeed in the market.However,it is not easy to r educe RRO,NRRO,and the weight of the spinning disk spindle system efficiently because lightweight construction and or bearing stiffness changes often yields a decrease in the static and dynamic stiffness of the system,and consequently hi gh vibrations may be generated as a results.Therefore,it is of importance to e valuate in advance the accurate dynamic behavior of the high speed spinning disk spindle system of a HDD sysem.This study introduces an optimum design of the high speed spinning disk spindle system of a HDD for minimum RRO,NRRO,and lightweight construction using a gene tic algorithm.The spinning disk,hub,and bearing components of a HDD system ar e modelled as appropriate finite elements respectively and their equations of mo tion are derived to construct the system equations of the whole spinning disk sp indle system of the HDD system.The RRO and NRRO responses of the spinning disk,due to exciting forces arised from ball bearing faults and rotating unbalance,are analyzed.In the design optimation,the hub thickness,the disk thickness,bearing positio ns(or bearing span)and bearing stiffness were set as design variables.The uni que objective function is obtained by multiplying an appropriate weighting facto r by multi-objective functions,such as RRO,NRRO,and the total weight of HDD the system.The constraints are maximum RRO limit,maximum weight linit,and the critical speed limit of the HDD spindle system.Results show that the RRO,NRRO,and weight are reduced by 6%,66.7%and 28%r espectively compared with the initial design of the HDD system.Therefore,thi s present study can be used for an optimum design of the spinning disk spindle s ystem of a HDD for lightweight construction and low vibrations.
文摘Aerodynamic optimization design of compressor blade shape is a design challenge at present because itis inherently a multiobjective problem. Thus, multiobjective Genetic Algorithms based on the multibranch simulated annealing selection and collection of Pareto solutions strategy have been developedand applied to the optimum design of compressor cascade. The present multiobjective design seeks highpressure rise, high flow turning angle and low total pressure loss at a low inlet Mach number. Paretosolutions obtain the better aerodynamic performance of the cascade than the existing Control DiffusionAirfoil. From the Pareto solutions, the decision maker would be able to find a design that satisfies hisdesign goal best. The results indicate that the feasibility of multiobjective Genetic Algorithms as amultiple objectives optimization tool in the engineering field.
基金Supported by the National Natural Science Foundation of China(No.52005441)Natural Science Foundation of Zhejiang Province(No.LQ21E050017)+4 种基金Young Elite Scientist Sponsorship Program by CAST(No.2022QNRC001)State Key Laboratory of Mechanical System and Vibration(No.MSV202316)"Pioneer"and"Leading Goose"R&D Program of Zhejiang Province(Nos.2022C01122,2022C01132)the Fundamental Research Funds for the Provincial Universities of Zhejiang(No.RFA2023007)the Research Project of ZJUT(No.GYY-ZH2023075).
文摘Hydraulic circuits with high speed on/off valve(HSV)for servo control have become commonplace in aerospace.However,the individual valve that is not volume-optimized results in a large total size of hydraulic control system,diminishing the practicality.To address this issue,the high-precision equivalent reluctance model of the HSV is established by employing an equivalent magnetic circuit,on which the dynamic characteristic of the HSV,as well as the effects of structural parameters on switching behaviour,are investigated.Based on this model,multi-objective optimization is adopted to design an HSV with faster dynamic performance and smaller volume,NSGA-II genetic algorithm is applied to obtain the Pareto front of the desired objectives.To assess the impact before and after optimization,an HSV based on the optimized structure is manufactured and tested.The experimental results show that the optimized HSV reduces 47.1%of its solenoid volume while improving opening and closing dynamic performance by 14.8%and 43.0%respectively,increasing maximum switching frequency by 6.2%,and expanding flow linear control area by 6.7%.These results validate the optimized structure and indicate that the optimization method provided in the paper is beneficial for developing superior HSV.
文摘In this paper we present a new optimization algorithm, and the proposed algorithm operates in two phases. In the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm is based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept e-dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems.
