In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective op...In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.展开更多
A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with t...A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.展开更多
The simulation of a product development process for concurrent engineering has beenmotivated by the desire to increase productivity by improving the product development pro-cess.In this paper,the IDEF3 process descrip...The simulation of a product development process for concurrent engineering has beenmotivated by the desire to increase productivity by improving the product development pro-cess.In this paper,the IDEF3 process description capture method is discussed.On the basisof IDEF3 method,a simulation system of the product development process for concurrent en-gineering is developed.The architecture of the simulation system is proposed.The simula-tion model is built using object-oriented approach.It employs an event scheduling approachto emulate the product development process.The simulation mechanism based on messagepassing:is also presented.展开更多
Estimation of distribution algorithms are a class of evolutionary optimization algorithms based on probability distribution model. In this article, a Pareto-based multi-objective estimation of distribution algorithm w...Estimation of distribution algorithms are a class of evolutionary optimization algorithms based on probability distribution model. In this article, a Pareto-based multi-objective estimation of distribution algorithm with multivariate T-copulas is proposed. The algorithm employs Pareto-based approach and multivariate T-copulas to construct probability distribution model. To estimate joint distribution of the selected solutions, the correlation matrix of T-copula is firstly estimated by estimating Kendall’s tau and using the relationship of Kendall’s tau and correlation matrix. After the correlation matrix is estimated, the degree of freedom of T-copula is estimated by using the maximum likelihood method. Afterwards, the Monte Carte simulation is used to generate new individuals. An archive with maximum capacity is used to maintain the non-dominated solutions. The Pareto optimal solutions are selected from the archive on the basis of the diversity of the solutions, and the crowding-distance measure is used for the diversity measurement. The archive gets updated with the inclusion of the non-dominated solutions from the combined population and current archive, and the archive which exceeds the maximum capacity is cut using the diversity consideration. The proposed algorithm is applied to some well-known benchmark. The relative experimental results show that the algorithm has better performance and is effective.展开更多
We investigate the teleportation of an entangled state via a couple of quantum channels, which are composed of a spin-1/2 Heisenberg dimer in two infinite Ising–Heisenberg chains. The heterotrimetallic coordination p...We investigate the teleportation of an entangled state via a couple of quantum channels, which are composed of a spin-1/2 Heisenberg dimer in two infinite Ising–Heisenberg chains. The heterotrimetallic coordination polymer CuⅡMnⅡ(L1)][FeⅢ(bpb)(CN)2]·ClO4·H2O(abbreviated as Fe–Mn–Cu) can be regarded as an actual material for this chain.We apply the transfer-matrix approach to obtain the density operator for the Heisenberg dimer and use the standard teleportation protocol to derive the analytical expression of the density matrix of the output state and the average fidelity of the entanglement teleportation. We study the effects of the temperature T, anisotropy coupling parameter △, Heisenberg coupling parameter J2 and external magnetic field h on the quantum channels. The results show that anisotropy coupling? and Heisenberg coupling J2 can favor the generation of the output concurrence and expand the scope of the successful average fidelity.展开更多
The mathematical model of optimal placement of active members in truss adaptive structures is essentially a nonlinear multi-objective optimization problem with mixed variables. It is usually much difficult and costly ...The mathematical model of optimal placement of active members in truss adaptive structures is essentially a nonlinear multi-objective optimization problem with mixed variables. It is usually much difficult and costly to be solved. In this paper, the optimal location of active members is treated in terms of （0, 1） discrete variables. Structural member sizes, control gains, and （0, 1） placement variables are treated simultaneously as design variables. Then, a succinct and reasonable compromise scalar model, which is transformed from original multi-objective optimization, is established, in which the （0, 1） discrete variables are converted into an equality constraint. Secondly, by penalty function approach, the subsequent scalar mixed variable compromise model can be formulated equivalently as a sequence of continuous variable problems. Thirdly, for each continuous problem in the sequence, by choosing intermediate design variables and temporary critical constraints, the approximation concept is carried out to generate a sequence of explicit approximate problems which enhance the quality of the approximate design problems. Considering the proposed method, a FORTRAN program OPAMTAS2.0 for optimal placement of active members in truss adaptive structures is developed, which is used by the constrained variable metric method with the watchdog technique （CVMW method）. Finally, a typical 18 bar truss adaptive structure as test numerical examples is presented to illustrate that the design methodology set forth is simple, feasible, efficient and stable. The established scalar mixed variable compromise model that can avoid the ill-conditioned possibility caused by the different orders of magnitude of various objective functions in optimization process, therefore, it enables the optimization algorithm to have a good stability. On the other hand, the proposed novel optimization technique can make both discrete and continuous variables be optimized simultaneously.展开更多
文摘In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.
基金supported by the Key International Cooperation Research Project(61720106003)the National Natural Science Foundation of China(62001517)+2 种基金the Shanghai Aerospace Science and Technology Innovation Foundation(SAST2019-095)the NUPTSF(NY220111)the Foundational Research Project of Complex Electronic System Simulation Laboratory(DXZT-JC-ZZ-2019-009,DXZTJC-ZZ-2019-005).
文摘A multi-objective optimization based robust beamforming(BF)scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle(UAV)network.Since the satellite network coexists with the UAV network,we first consider both achievable secrecy rate maximization and total transmit power minimization,and formulate a multi-objective optimization problem(MOOP)using the weighted Tchebycheff approach.Then,by supposing that only imperfect channel state information based on the angular information is available,we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones.Next,we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector.Finally,simulation results illustrate that the Pareto optimal trade-off can be achieved,and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.
基金Supported by the High Technology Research and Development Programme of China.
文摘The simulation of a product development process for concurrent engineering has beenmotivated by the desire to increase productivity by improving the product development pro-cess.In this paper,the IDEF3 process description capture method is discussed.On the basisof IDEF3 method,a simulation system of the product development process for concurrent en-gineering is developed.The architecture of the simulation system is proposed.The simula-tion model is built using object-oriented approach.It employs an event scheduling approachto emulate the product development process.The simulation mechanism based on messagepassing:is also presented.
文摘Estimation of distribution algorithms are a class of evolutionary optimization algorithms based on probability distribution model. In this article, a Pareto-based multi-objective estimation of distribution algorithm with multivariate T-copulas is proposed. The algorithm employs Pareto-based approach and multivariate T-copulas to construct probability distribution model. To estimate joint distribution of the selected solutions, the correlation matrix of T-copula is firstly estimated by estimating Kendall’s tau and using the relationship of Kendall’s tau and correlation matrix. After the correlation matrix is estimated, the degree of freedom of T-copula is estimated by using the maximum likelihood method. Afterwards, the Monte Carte simulation is used to generate new individuals. An archive with maximum capacity is used to maintain the non-dominated solutions. The Pareto optimal solutions are selected from the archive on the basis of the diversity of the solutions, and the crowding-distance measure is used for the diversity measurement. The archive gets updated with the inclusion of the non-dominated solutions from the combined population and current archive, and the archive which exceeds the maximum capacity is cut using the diversity consideration. The proposed algorithm is applied to some well-known benchmark. The relative experimental results show that the algorithm has better performance and is effective.
基金Project supported by the National Natural Science Foundation of China(Grant No.11274102)the New Century Excellent Talents in University of Ministry of Education of China(Grant No.NCET-11-0960)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20134208110001)
文摘We investigate the teleportation of an entangled state via a couple of quantum channels, which are composed of a spin-1/2 Heisenberg dimer in two infinite Ising–Heisenberg chains. The heterotrimetallic coordination polymer CuⅡMnⅡ(L1)][FeⅢ(bpb)(CN)2]·ClO4·H2O(abbreviated as Fe–Mn–Cu) can be regarded as an actual material for this chain.We apply the transfer-matrix approach to obtain the density operator for the Heisenberg dimer and use the standard teleportation protocol to derive the analytical expression of the density matrix of the output state and the average fidelity of the entanglement teleportation. We study the effects of the temperature T, anisotropy coupling parameter △, Heisenberg coupling parameter J2 and external magnetic field h on the quantum channels. The results show that anisotropy coupling? and Heisenberg coupling J2 can favor the generation of the output concurrence and expand the scope of the successful average fidelity.
基金supported by National Natural Science Foundation of China(Grant No.10472007)
文摘The mathematical model of optimal placement of active members in truss adaptive structures is essentially a nonlinear multi-objective optimization problem with mixed variables. It is usually much difficult and costly to be solved. In this paper, the optimal location of active members is treated in terms of （0, 1） discrete variables. Structural member sizes, control gains, and （0, 1） placement variables are treated simultaneously as design variables. Then, a succinct and reasonable compromise scalar model, which is transformed from original multi-objective optimization, is established, in which the （0, 1） discrete variables are converted into an equality constraint. Secondly, by penalty function approach, the subsequent scalar mixed variable compromise model can be formulated equivalently as a sequence of continuous variable problems. Thirdly, for each continuous problem in the sequence, by choosing intermediate design variables and temporary critical constraints, the approximation concept is carried out to generate a sequence of explicit approximate problems which enhance the quality of the approximate design problems. Considering the proposed method, a FORTRAN program OPAMTAS2.0 for optimal placement of active members in truss adaptive structures is developed, which is used by the constrained variable metric method with the watchdog technique （CVMW method）. Finally, a typical 18 bar truss adaptive structure as test numerical examples is presented to illustrate that the design methodology set forth is simple, feasible, efficient and stable. The established scalar mixed variable compromise model that can avoid the ill-conditioned possibility caused by the different orders of magnitude of various objective functions in optimization process, therefore, it enables the optimization algorithm to have a good stability. On the other hand, the proposed novel optimization technique can make both discrete and continuous variables be optimized simultaneously.
