The uncertainty of time, quantity and quality of recycling products leads tothe bad stability and flexibility of remanufacturing logistics networks, and general design onlycovered the minimizing logistics cost, thus, ...The uncertainty of time, quantity and quality of recycling products leads tothe bad stability and flexibility of remanufacturing logistics networks, and general design onlycovered the minimizing logistics cost, thus, robust design is presented here to solve theuncertainty. The mathematical model of remanufacturing logistics networks is built based onstochastic distribution of uncontrollable factors, and robust objectives are presented. Theintegration of mathematical simulation and design of experiment method is performed to do sensitiveanalysis. The influence of each factor and level on the system is investigated, and the main factorsand optimum combination are studied. The numbers of factors, level of each factor and designprocess of experiment are investigated as well. Finally, the process of robust design based ondesign of experiment is demonstrated by a detailed example.展开更多
Robust optimization approach for aerodynamic design has been developed and applied to supercritical wing aerodynamic design. The aerodynamic robust optimization design system consists of genetic optimization algorithm...Robust optimization approach for aerodynamic design has been developed and applied to supercritical wing aerodynamic design. The aerodynamic robust optimization design system consists of genetic optimization algorithm, improved back propagation （BP） neural network and deformation grid technology. In this article, the BP neural network has been improved in two major aspects to enhance the training speed and precision. Uniformity sampling is adopted to generate samples which will be used to establish surrogate model. The testing results show that the prediction precision of the improved BP neural network is reliable. On the assumption that the law of Mach number obeys normal distribution, supercritical wing configuration considering fuselage interfering of a certain aerobus has been taken as a typical example, and five design sections and twist angles have been optimized. The results show that the optimized wing, which considers robust design, has better aerodynamic characteristics. What＇s more, the intensity of shock wave has been reduced.展开更多
This paper introduced a robust parameter coordination method to analyze parameter uncertainties so as to predict conflicts and coordinate parameters in multidisciplinary design. The proposed method is based on constra...This paper introduced a robust parameter coordination method to analyze parameter uncertainties so as to predict conflicts and coordinate parameters in multidisciplinary design. The proposed method is based on constraints network, which gives a formulated model to analyze the coupling effects between design variables and product specifications. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. To solve this constraint network model, a general consistent algorithm framework is designed and implemented with interval arithmetic and the genetic algorithm, which can deal with both algebraic and ordinary differential equations. With the help of this method, designers could infer the consistent solution space from the given specifications. A case study involving the design of a bogie dumping system demonstrates the usefulness of this approach.展开更多
A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimizati...A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.展开更多
New synchronization algorithm and analysis of its convergence rate for clock oscillators in dynamical network with time-delays are presented.A network of nodes equipped with hardware clock oscillators with bounded dri...New synchronization algorithm and analysis of its convergence rate for clock oscillators in dynamical network with time-delays are presented.A network of nodes equipped with hardware clock oscillators with bounded drift is considered.Firstly,a dynamic synchronization algorithm based on consensus control strategy,namely fast averaging synchronization algorithm （FASA）,is presented to find the solutions to the synchronization problem.By FASA,each node computes the logical clock value based on its value of hardware clock and message exchange.The goal is to synchronize all the nodes＇ logical clocks as closely as possible.Secondly,the convergence rate of FASA is analyzed that proves it is related to the bound by a nondecreasing function of the uncertainty in message delay and network parameters.Then,FASA＇s convergence rate is proven by means of the robust optimal design.Meanwhile,several practical applications for FASA,especially the application to inverse global positioning system （IGPS） base station network are discussed.Finally,numerical simulation results demonstrate the correctness and efficiency of the proposed FASA.Compared FASA with traditional clock synchronization algorithms （CSAs）,the convergence rate of the proposed algorithm converges faster than that of the CSAs evidently.展开更多
A robust airfoil optimization platform is constructed based on the modified particle swarm optimization method （i.e., the second-order oscillating particle swarm method）, which consists of an efficient optimization ...A robust airfoil optimization platform is constructed based on the modified particle swarm optimization method （i.e., the second-order oscillating particle swarm method）, which consists of an efficient optimization algorithm, a precise aerodynamic analysis program, a high accuracy surrogate model, and a classical airfoil parametric method. There are two improvements for the modified particle swarm method compared with the standard particle swarm method. First, the particle velocity is represented by the combination of the particle position and the variation of position, which makes the particle swarm algorithm a second-order precision method with respect to the particle po- sition. Second, for the sake of adding diversity to the swarm and enlarging the parameter searching domain to improve the global convergence performance of the algorithm, an oscillating term is introduced to the update formula of the particle velocity. At last, tak- ing two airfoils as examples, the aerodynamic shapes are optimized on this optimization platform. It is shown from the optimization results that the aerodynamic characteristic of the airfoils is greatly improved in a broad design range.展开更多
基金This project is supported by Provincial Natural Science Foundation of Shanghai, China (No. 02ZH14060).
文摘The uncertainty of time, quantity and quality of recycling products leads tothe bad stability and flexibility of remanufacturing logistics networks, and general design onlycovered the minimizing logistics cost, thus, robust design is presented here to solve theuncertainty. The mathematical model of remanufacturing logistics networks is built based onstochastic distribution of uncontrollable factors, and robust objectives are presented. Theintegration of mathematical simulation and design of experiment method is performed to do sensitiveanalysis. The influence of each factor and level on the system is investigated, and the main factorsand optimum combination are studied. The numbers of factors, level of each factor and designprocess of experiment are investigated as well. Finally, the process of robust design based ondesign of experiment is demonstrated by a detailed example.
文摘Robust optimization approach for aerodynamic design has been developed and applied to supercritical wing aerodynamic design. The aerodynamic robust optimization design system consists of genetic optimization algorithm, improved back propagation （BP） neural network and deformation grid technology. In this article, the BP neural network has been improved in two major aspects to enhance the training speed and precision. Uniformity sampling is adopted to generate samples which will be used to establish surrogate model. The testing results show that the prediction precision of the improved BP neural network is reliable. On the assumption that the law of Mach number obeys normal distribution, supercritical wing configuration considering fuselage interfering of a certain aerobus has been taken as a typical example, and five design sections and twist angles have been optimized. The results show that the optimized wing, which considers robust design, has better aerodynamic characteristics. What＇s more, the intensity of shock wave has been reduced.
基金National Natural Science Foundation of China(No. 60304015, No. 50575142)
文摘This paper introduced a robust parameter coordination method to analyze parameter uncertainties so as to predict conflicts and coordinate parameters in multidisciplinary design. The proposed method is based on constraints network, which gives a formulated model to analyze the coupling effects between design variables and product specifications. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. To solve this constraint network model, a general consistent algorithm framework is designed and implemented with interval arithmetic and the genetic algorithm, which can deal with both algebraic and ordinary differential equations. With the help of this method, designers could infer the consistent solution space from the given specifications. A case study involving the design of a bogie dumping system demonstrates the usefulness of this approach.
基金This project is supported by National Natural Science Foundation of China (No.60304015, No.50575142).
文摘A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.
基金Sponsored by the Cooperation Building Foundation Project of Beijing Education Committee (100070
文摘New synchronization algorithm and analysis of its convergence rate for clock oscillators in dynamical network with time-delays are presented.A network of nodes equipped with hardware clock oscillators with bounded drift is considered.Firstly,a dynamic synchronization algorithm based on consensus control strategy,namely fast averaging synchronization algorithm （FASA）,is presented to find the solutions to the synchronization problem.By FASA,each node computes the logical clock value based on its value of hardware clock and message exchange.The goal is to synchronize all the nodes＇ logical clocks as closely as possible.Secondly,the convergence rate of FASA is analyzed that proves it is related to the bound by a nondecreasing function of the uncertainty in message delay and network parameters.Then,FASA＇s convergence rate is proven by means of the robust optimal design.Meanwhile,several practical applications for FASA,especially the application to inverse global positioning system （IGPS） base station network are discussed.Finally,numerical simulation results demonstrate the correctness and efficiency of the proposed FASA.Compared FASA with traditional clock synchronization algorithms （CSAs）,the convergence rate of the proposed algorithm converges faster than that of the CSAs evidently.
文摘A robust airfoil optimization platform is constructed based on the modified particle swarm optimization method （i.e., the second-order oscillating particle swarm method）, which consists of an efficient optimization algorithm, a precise aerodynamic analysis program, a high accuracy surrogate model, and a classical airfoil parametric method. There are two improvements for the modified particle swarm method compared with the standard particle swarm method. First, the particle velocity is represented by the combination of the particle position and the variation of position, which makes the particle swarm algorithm a second-order precision method with respect to the particle po- sition. Second, for the sake of adding diversity to the swarm and enlarging the parameter searching domain to improve the global convergence performance of the algorithm, an oscillating term is introduced to the update formula of the particle velocity. At last, tak- ing two airfoils as examples, the aerodynamic shapes are optimized on this optimization platform. It is shown from the optimization results that the aerodynamic characteristic of the airfoils is greatly improved in a broad design range.
基金the National Natural Science Foundation of China(71171129,71301101)the Specialized Research Fund for the Doctoral Program of Higher Education of China(20123121110004)
