The tighten couplings of game strategies with adjoint methods for multi-criterion aerodynamic design optimization are ad-dressed. Its numerical implementation is also described in details. In cooperative game,adjoint ...The tighten couplings of game strategies with adjoint methods for multi-criterion aerodynamic design optimization are ad-dressed. Its numerical implementation is also described in details. In cooperative game,adjoint methods are coupled in parallel to compute Pareto front collaboratively. Conversely in a Nash game,adjoint methods are coupled in each player s decision making to achieve Nash equilibrium competitively. In Stackelberg game,adjoint methods used by players are nested hierarchically through incomp...展开更多
Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary a...Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.展开更多
The suboptimal reliable guaranteed cost control （RGCC） with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fauk model in sensors, which considers o...The suboptimal reliable guaranteed cost control （RGCC） with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fauk model in sensors, which considers outage or partial degradation of sensors, is adopted. The influence of the disturbance on the quadratic stability of the closed-loop systems is analyzed. The reliable state-feedback controller is developed by a linear matrix inequalities （LMIs） approach, to minimize the upper bound of a quadratic cost fimction under the conditions that all the closed-loop poles be placed in a specified disk, and that the prescribed level of H∞ disturbance attenuation and the upper bound constraints of control inputs＇ magnitudes be guaranteed. Thus, with the above muki-criterion constraints, the resulting closed-loop system can provide satisfactory stability, transient property, a disturbance rejection level and minimized quadratic cost performance despite possible sensor faults.展开更多
A method for optimizing automotive doors under multiple criteria involving the side impact, stiffness, natural frequency, and structure weight is presented. Metamodeling technique is employed to construct approximatio...A method for optimizing automotive doors under multiple criteria involving the side impact, stiffness, natural frequency, and structure weight is presented. Metamodeling technique is employed to construct approximations to replace the high computational simulation models. The approximating functions for stiffness and natural frequency are constructed using Taylor series approximation. Three popular approximation techniques,i.e.polynomial response surface (PRS), stepwise regression (SR), and Kriging are studied on their accuracy in the construction of side impact functions. Uniform design is employed to sample the design space of the door impact analysis. The optimization problem is solved by a multi-objective genetic algorithm. It is found that SR technique is superior to PRS and Kriging techniques in terms of accuracy in this study. The numerical results demonstrate that the method successfully generates a well-spread Pareto optimal set. From this Pareto optimal set, decision makers can select the most suitable design according to the vehicle program and its application.展开更多
Despite the planned installation and operations of the traditional IEEE 802.11 networks,they still experience degraded performance due to the number of inefficiencies.One of the main reasons is the received signal str...Despite the planned installation and operations of the traditional IEEE 802.11 networks,they still experience degraded performance due to the number of inefficiencies.One of the main reasons is the received signal strength indicator(RSSI)association problem,in which the user remains connected to the access point(AP)unless the RSSI becomes too weak.In this paper,we propose a multi-criterion association(WiMA)scheme based on software defined networking(SDN)in Wi-Fi networks.An association solution based on multi-criterion such as AP load,RSSI,and channel occupancy is proposed to satisfy the quality of service(QoS).SDNhaving an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance.To implementWiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator.The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30%and enhances the throughput by 20%–50%,hence maintaining user fairness and accommodating more wireless devices and traffic load in the network,when compared to traditional client-driven(CD)approach and state of the art Wi-Balance approach.展开更多
In this work, we consider a specific problem of optimal planning of maritime transportation of multiproduct cargo by ships of one （so-called ＂corporate strategy＂） or several （so-called ＂partially corporate strat...In this work, we consider a specific problem of optimal planning of maritime transportation of multiproduct cargo by ships of one （so-called ＂corporate strategy＂） or several （so-called ＂partially corporate strategy＂） companies： the core of the problem consists of the existence of the network of intermediate seaports （i.e., transitional seaports）, where for every ship arrived the cargo handling is done, and which are situated between the starting and the finishing seaports. In this work, there are mathematical models built from scratch in the form of multi-criterion optimization problem; according to the properties of the criteria and structure of the feasible solution set; are formulated different optimality conditions; are analysed different approaches for finding effective solutions （i.e., Pareto optimal solutions） and for check of the given solutions＇ effectiveness. In addition, in this work, there is considered and analysed well-known method of contraction of the Pareto boundary （goal attainment method of Gembicki）, then, it is used for reducing the built models to a one-criterion problem of linear programming.展开更多
Health indicator(HI)construction is a crucial task in degradation evaluation and facilitates the prognostic and health management(PHM)of rotating machinery.Excluding interference from artificial labeling,the HI constr...Health indicator(HI)construction is a crucial task in degradation evaluation and facilitates the prognostic and health management(PHM)of rotating machinery.Excluding interference from artificial labeling,the HI construction approaches in an unsupervised manner have attracted substantial attention.Nevertheless,current unsupervised methods generally struggle with two problems:(1)ignorance of both redundancy between features and global variability of features during the feature selection process;(2)inadequate utilization of information from different sampling moments.To tackle these problems,this work develops a novel unsupervised approach for HI construction that integrates multi-criterion feature selection and the Attentive Variational Autoencoder(Attentive VAE).Explicitly,a multi-criterion feature selection(Mc FS)algorithm together with an elaborately designed metric is proposed to determine a superior feature subset,considering the relevance,the redundancy,and the global variability of features simultaneously.Then,for the adequate utilization of the information from distinct sampling moments,a deep learning model named Attentive VAE is established.The Attentive VAE is solely fed with the selected features in the health state for model training and the HI is derived through the reconstruction error to reveal the degradation degree of machinery.Two case studies based on genuine experimental datasets are involved to quantitatively evaluate the superiority of the developed approach,demonstrating its superiority over other unsupervised methods for characterizing degradation processes.The effectiveness of both the Mc FS algorithm and the Attentive VAE is verified by ablation experiments,respectively.展开更多
In this paper,computational models of environmental pollution and energy consumption of urban multimodal traffic network are proposed according to pertinent research and a multi-objective programming model is then dev...In this paper,computational models of environmental pollution and energy consumption of urban multimodal traffic network are proposed according to pertinent research and a multi-objective programming model is then developed to formulate optimization problem for such a system.Simultaneously,the main factors,such as travel time,pricing and convenience which influence travelers' choice behaviors are all considered and a combined assignment model is proposed to simulate travelers' mode and route choices.A bi-level programming model,in which the multi-objective optimization model is treated as the upper-level problem and the combined assignment model is processed as the lower-level problem,is then presented to solve multi-criterion system optimization problem for urban multimodal traffic network.The solution algorithms of the proposed models are also presented.Finally,the model and its algorithms are illustrated through a simple numerical example.展开更多
This paper introduces the virtual and real game concepts to investigate multi-criterion optimization for optimum shape design in aerodynamics. The constrained adjoint meth- odology is used as the basic optimizer. Furt...This paper introduces the virtual and real game concepts to investigate multi-criterion optimization for optimum shape design in aerodynamics. The constrained adjoint meth- odology is used as the basic optimizer. Furthermore, the above is combined with the vir- tual and real game strategies to treat single-point/multi-point airfoil optimization. In a symmetric Nash Game, each optimizer attempts to optimize one’s own target with ex- change of symmetric information with others. A Nash equilibrium is just the compromised solution among the multiple criteria. Several kinds of airfoil splitting and design cases are shown for the utility of virtual and real game strategies in aerodynamic design. Successful design results confirm the validity and efficiency of the present design method.展开更多
实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(g...实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(geschgorin disk estimator,GDE)准则联合多重信号分类(multiple signal classification,MUSIC)算法的变压器局部放电多目标定位方法。首先,利用改进盖氏圆准则确定真实放电源数目;然后,在信源数确定的情况下利用MUSIC算法对多个局部放电源的波达方向进行估计。仿真结果表明,本方法定位精度高,且在白噪声和空间色噪声的情况下仍能对放电源的俯仰角和方位角进行准确估计,能够满足实际工程需求。展开更多
基金National Natural Science Foundation of China (10872093)
文摘The tighten couplings of game strategies with adjoint methods for multi-criterion aerodynamic design optimization are ad-dressed. Its numerical implementation is also described in details. In cooperative game,adjoint methods are coupled in parallel to compute Pareto front collaboratively. Conversely in a Nash game,adjoint methods are coupled in each player s decision making to achieve Nash equilibrium competitively. In Stackelberg game,adjoint methods used by players are nested hierarchically through incomp...
文摘Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.
基金the National Natural Science Foundation of China (No. 60574082)the National Creative Research Groups Sci-ence Foundation of China (No. 60721062)the China Postdoc-toral Science Foundation (No. 20070411178)
文摘The suboptimal reliable guaranteed cost control （RGCC） with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fauk model in sensors, which considers outage or partial degradation of sensors, is adopted. The influence of the disturbance on the quadratic stability of the closed-loop systems is analyzed. The reliable state-feedback controller is developed by a linear matrix inequalities （LMIs） approach, to minimize the upper bound of a quadratic cost fimction under the conditions that all the closed-loop poles be placed in a specified disk, and that the prescribed level of H∞ disturbance attenuation and the upper bound constraints of control inputs＇ magnitudes be guaranteed. Thus, with the above muki-criterion constraints, the resulting closed-loop system can provide satisfactory stability, transient property, a disturbance rejection level and minimized quadratic cost performance despite possible sensor faults.
基金Supported by National"863"Program of China (No.2006AA04Z127) .
文摘A method for optimizing automotive doors under multiple criteria involving the side impact, stiffness, natural frequency, and structure weight is presented. Metamodeling technique is employed to construct approximations to replace the high computational simulation models. The approximating functions for stiffness and natural frequency are constructed using Taylor series approximation. Three popular approximation techniques,i.e.polynomial response surface (PRS), stepwise regression (SR), and Kriging are studied on their accuracy in the construction of side impact functions. Uniform design is employed to sample the design space of the door impact analysis. The optimization problem is solved by a multi-objective genetic algorithm. It is found that SR technique is superior to PRS and Kriging techniques in terms of accuracy in this study. The numerical results demonstrate that the method successfully generates a well-spread Pareto optimal set. From this Pareto optimal set, decision makers can select the most suitable design according to the vehicle program and its application.
基金supported by the“Human Resources Program in Energy Technology”of the Korea Institute of Energy Technology Evaluation and Planning(KETEP),granted financial resources from the Ministry of Trade,Industry&Energy,Republic of Korea(No.20204010600090).
文摘Despite the planned installation and operations of the traditional IEEE 802.11 networks,they still experience degraded performance due to the number of inefficiencies.One of the main reasons is the received signal strength indicator(RSSI)association problem,in which the user remains connected to the access point(AP)unless the RSSI becomes too weak.In this paper,we propose a multi-criterion association(WiMA)scheme based on software defined networking(SDN)in Wi-Fi networks.An association solution based on multi-criterion such as AP load,RSSI,and channel occupancy is proposed to satisfy the quality of service(QoS).SDNhaving an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance.To implementWiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator.The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30%and enhances the throughput by 20%–50%,hence maintaining user fairness and accommodating more wireless devices and traffic load in the network,when compared to traditional client-driven(CD)approach and state of the art Wi-Balance approach.
文摘In this work, we consider a specific problem of optimal planning of maritime transportation of multiproduct cargo by ships of one （so-called ＂corporate strategy＂） or several （so-called ＂partially corporate strategy＂） companies： the core of the problem consists of the existence of the network of intermediate seaports （i.e., transitional seaports）, where for every ship arrived the cargo handling is done, and which are situated between the starting and the finishing seaports. In this work, there are mathematical models built from scratch in the form of multi-criterion optimization problem; according to the properties of the criteria and structure of the feasible solution set; are formulated different optimality conditions; are analysed different approaches for finding effective solutions （i.e., Pareto optimal solutions） and for check of the given solutions＇ effectiveness. In addition, in this work, there is considered and analysed well-known method of contraction of the Pareto boundary （goal attainment method of Gembicki）, then, it is used for reducing the built models to a one-criterion problem of linear programming.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFB3400700)the China Academy of Railway Sciences Corporation Limited within the major issues of the fund(Grant No.2021YJ212)+1 种基金the National Natural Science Foundation of China(Grant Nos.12072188,12121002)the Natural Science Foundation of Shanghai(Grant No.20ZR1425200)。
文摘Health indicator(HI)construction is a crucial task in degradation evaluation and facilitates the prognostic and health management(PHM)of rotating machinery.Excluding interference from artificial labeling,the HI construction approaches in an unsupervised manner have attracted substantial attention.Nevertheless,current unsupervised methods generally struggle with two problems:(1)ignorance of both redundancy between features and global variability of features during the feature selection process;(2)inadequate utilization of information from different sampling moments.To tackle these problems,this work develops a novel unsupervised approach for HI construction that integrates multi-criterion feature selection and the Attentive Variational Autoencoder(Attentive VAE).Explicitly,a multi-criterion feature selection(Mc FS)algorithm together with an elaborately designed metric is proposed to determine a superior feature subset,considering the relevance,the redundancy,and the global variability of features simultaneously.Then,for the adequate utilization of the information from distinct sampling moments,a deep learning model named Attentive VAE is established.The Attentive VAE is solely fed with the selected features in the health state for model training and the HI is derived through the reconstruction error to reveal the degradation degree of machinery.Two case studies based on genuine experimental datasets are involved to quantitatively evaluate the superiority of the developed approach,demonstrating its superiority over other unsupervised methods for characterizing degradation processes.The effectiveness of both the Mc FS algorithm and the Attentive VAE is verified by ablation experiments,respectively.
基金supported by the National Natural Science Foundation of China (Grant Nos. 71071016, 70901005)the Fundamental Research Funds for the Central Universities (Grant Nos. 2009JBM040 and 2009JBZ012)funded by a Discovery Grant (Application No. 342485-07) from the Natural Science and Engineering Research Council (NSERC), Canada
文摘In this paper,computational models of environmental pollution and energy consumption of urban multimodal traffic network are proposed according to pertinent research and a multi-objective programming model is then developed to formulate optimization problem for such a system.Simultaneously,the main factors,such as travel time,pricing and convenience which influence travelers' choice behaviors are all considered and a combined assignment model is proposed to simulate travelers' mode and route choices.A bi-level programming model,in which the multi-objective optimization model is treated as the upper-level problem and the combined assignment model is processed as the lower-level problem,is then presented to solve multi-criterion system optimization problem for urban multimodal traffic network.The solution algorithms of the proposed models are also presented.Finally,the model and its algorithms are illustrated through a simple numerical example.
基金the National Natural Science Foundation of China (Grant No.10372040)
文摘This paper introduces the virtual and real game concepts to investigate multi-criterion optimization for optimum shape design in aerodynamics. The constrained adjoint meth- odology is used as the basic optimizer. Furthermore, the above is combined with the vir- tual and real game strategies to treat single-point/multi-point airfoil optimization. In a symmetric Nash Game, each optimizer attempts to optimize one’s own target with ex- change of symmetric information with others. A Nash equilibrium is just the compromised solution among the multiple criteria. Several kinds of airfoil splitting and design cases are shown for the utility of virtual and real game strategies in aerodynamic design. Successful design results confirm the validity and efficiency of the present design method.
文摘实际变压器局部放电定位过程中放电源数目是未知的,常利用传统高分辨波达方向(direction of arrival,DOA)估计算法解决放电定位问题,但在信源数欠估计、过估计情况下存在定位精度低、误差大的问题。为此,本文提出了一种基于改进盖氏圆(geschgorin disk estimator,GDE)准则联合多重信号分类(multiple signal classification,MUSIC)算法的变压器局部放电多目标定位方法。首先,利用改进盖氏圆准则确定真实放电源数目;然后,在信源数确定的情况下利用MUSIC算法对多个局部放电源的波达方向进行估计。仿真结果表明,本方法定位精度高,且在白噪声和空间色噪声的情况下仍能对放电源的俯仰角和方位角进行准确估计,能够满足实际工程需求。
