A decision support system, including a multi-objective optimization framework and a multi-attribute decision making approach is proposed for satellite equipment layout. Firstly, given three objectives (to minimize the...A decision support system, including a multi-objective optimization framework and a multi-attribute decision making approach is proposed for satellite equipment layout. Firstly, given three objectives (to minimize the C.G. offset, the cross moments of inertia and the space debris impact risk), we develop a threedimensional layout optimization model. Unlike most of the previous works just focusing on mass characteristics of the system, a space debris impact risk index is developed. Secondly, we develop an efficient optimization framework for the integration of computer-aided design (CAD) software as well as the optimization algorithm to obtain the Pareto front of the layout optimization problem. Thirdly, after obtaining the candidate solutions, we present a multi-attribute decision making approach, which integrates the smart Pareto filter and the correlation coefficient and standard deviation (CCSD) method to select the best tradeoff solutions on the optimal Pareto fronts. Finally, the framework and the decision making approach are applied to a case study of a satellite platform.展开更多
A fuzzy particle swarm optimization （PSO） on the basis of elite archiving is proposed for solving multi-objective optimization problems. First, a new perturbation operator is designed, and the concepts of fuzzy glob...A fuzzy particle swarm optimization （PSO） on the basis of elite archiving is proposed for solving multi-objective optimization problems. First, a new perturbation operator is designed, and the concepts of fuzzy global best and fuzzy personal best are given on basis of the new operator. After that, particle updating equations are revised on the basis of the two new concepts to discourage the premature convergence and enlarge the potential search space; second, the elite archiving technique is used during the process of evolution, namely, the elite particles are introduced into the swarm, whereas the inferior particles are deleted. Therefore, the quality of the swarm is ensured. Finally, the convergence of this swarm is proved. The experimental results show that the nondominated solutions found by the proposed algorithm are uniformly distributed and widely spread along the Pareto front.展开更多
The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previ...The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previously,they were set by the technical workers according to the offline analysis results and an empirical formula,which leads to unstable process indices and high consumption frequently.So,a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives,where the key technical indices are predicted based on the digestion kinetics of diaspore.A multi-objective state transition algorithm(MOSTA)is improved to solve the problem,in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm.Then a rule based strategy is designed to make the final decision from the Pareto frontiers.The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production.Results show that the proposed method can achieve the technical target while reducing the energy consumption.展开更多
To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov pr...To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov process, so that the air combat situation can be effectively calculated via Bayesian inference theory. According to the situation assessment result,adaptively adjusts the weights of maneuver decision factors, which makes the objective function more reasonable and ensures the superiority situation for UCAV. As the air combat game is characterized by highly dynamic and a significant amount of uncertainty,to enhance the robustness and effectiveness of maneuver decision results, fuzzy logic is used to build the functions of four maneuver decision factors. Accuracy prediction of opponent aircraft is also essential to ensure making a good decision; therefore, a prediction model of opponent aircraft is designed based on the elementary maneuver method. Finally, the moving horizon optimization strategy is used to effectively model the whole air combat maneuver decision process. Various simulations are performed on typical scenario test and close-in dogfight, the results sufficiently demonstrate the superiority of the designed maneuver decision method.展开更多
To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description ab...To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.展开更多
This paper puts forward a new integrated design met ho d based on fuzzy matter-element optimization.On the based of analyzing the mod el of multi-objective fuzzy matter-element , the paper defines the m atter-element ...This paper puts forward a new integrated design met ho d based on fuzzy matter-element optimization.On the based of analyzing the mod el of multi-objective fuzzy matter-element , the paper defines the m atter-element weightily and changes solving multi-objective fuzzy optimization into solving dependent function K(x) of the single-objective optimization according to the optimization criterion. The paper particularly describes the realization approach of GA process of multi -objective fuzzy matter-element optimization: encode, produce initial populati on, confirm fitness function, select operator, etc. In the process, the adaptive macro genetic algorithms (AMGA) is applied to enhancing the evolution speed. Th e paper improves the two genetic operators: crossover and mutation operator. The modified adaptive macro genetic algorithms (MAMGA) is put forward simultane ously. It is adopted to solve the optimization problem. Three optimization methods, namely fuzzy matter-element optimization method, li nearity weighted method and fuzzy optimization method, are compared by using the table and figure, it shows that not only MAMGA is a little better than the AMGA , but also it reaches the extent to which the effective iteration generation is 62.2% of simple genetic algorithms (SGA). By the calculation of optimum exam ple, the improved method of genetic in the paper is much better than the method in reference of paper.展开更多
This paper presents a fuzzy sequential optimization method for the antenna structures with multiple objectives (structural displacement, weight, cost, nature frequency characteristic) based on fuzzy sets. This has led...This paper presents a fuzzy sequential optimization method for the antenna structures with multiple objectives (structural displacement, weight, cost, nature frequency characteristic) based on fuzzy sets. This has led to a set of new concepts which are discussed here. The paper establishes a sequential optimization model, in which the cost function is constructed, the membership function of single objective is defined as extended quadratic function, the membership function in decision making is constructed with linearly weighted and power product weighted models and the objectives are classed. In addition, the paper presents two methods, namely the linear extended method and the secondary constrained sequential optimization method, by which effective satisfactory design can be found. A computer program is given, optimization computing of the truss- type and antenna structures are described. It is shown that the method is practical and effective.展开更多
Predictive control has recently received much attention from researchers. However a challenging problem to be solved is how to tune the parameters of the predictive controller. So far, only few guidelines related to t...Predictive control has recently received much attention from researchers. However a challenging problem to be solved is how to tune the parameters of the predictive controller. So far, only few guidelines related to tuning of the parameters of predictive controllers have been provided in literature. In practice, these parameters are generally off-line determined by the designers' experience. From the point of view of process control, it is difficult to find out the optimal parameters for the control system based on a single quadratic performance index, which is used in the standard predictive control algorithm. The fuzzy decision-making function is investigated in this paper. Firstly, M control actions are achieved by unconstrained predictive control algorithm, and fuzzy goals and fuzzy constraints are then calculated and the global satisfaction degree is obtained by fuzzy inference. Moreover, the weighting coefficient λ in the cost function is tuned using simulation optimization according to the fuzzy criteria.展开更多
针对未来月面着陆动力下降段轨迹规划需综合考虑多性能指标的问题,提出一种对飞行轨迹先优化后决策的多目标轨迹规划方法.在多目标进化算法MOEA/D-AWA(multi-objective evolutionary algorithm based on decomposition with adaptive we...针对未来月面着陆动力下降段轨迹规划需综合考虑多性能指标的问题,提出一种对飞行轨迹先优化后决策的多目标轨迹规划方法.在多目标进化算法MOEA/D-AWA(multi-objective evolutionary algorithm based on decomposition with adaptive weight adjustment)的框架下对轨迹规划的多个指标进行分解,得到若干个单指标的子问题.将凸优化算法作为求解单目标轨迹优化子问题的底层算法,嵌套在MOEA/D-AWA的框架中,经过迭代优化获得一组动力下降段飞行轨迹,其构成多目标轨迹规划问题的帕累托最优解集.根据模糊决策理论对各个帕累托最优解对应的多个轨迹指标逐步降阶并进行综合评估,经过决策得到多指标约束下的飞行轨迹.仿真实验表明,该轨迹规划方法能够在综合多目标的情况下,优化获得一组动力下降轨迹集合,且能够根据不同任务要求从中决策出最优的动力下降段轨迹,可有效解决月面飞行器的多目标轨迹规划问题.展开更多
为了解决在实际决策时,由于知识背景不同决策者采用不同粒度语言术语集来表达而导致决策结果不准确的问题,本文提出了一种基于多粒度犹豫模糊语言术语集的逼近理想解排序(technique for order preference by similarity to ideal soluti...为了解决在实际决策时,由于知识背景不同决策者采用不同粒度语言术语集来表达而导致决策结果不准确的问题,本文提出了一种基于多粒度犹豫模糊语言术语集的逼近理想解排序(technique for order preference by similarity to ideal solution,TOPSIS)决策方法。首先选用各术语集中的最大粒度作为标准粒度,通过转换算法将每个决策者的语言术语集转换到同一标准粒度下进行集结,得出相应的隶属度语言术语集;然后结合TOPSIS方法,计算每个备选方案与正、负理想点距离,以相对贴近度的大小排序实现最优方案的选择;最后,通过一个实例,验证该方法的可行性和优越性。本文所提方法可应用于最优方案的选择问题中,提升决策结果准确度。展开更多
基金supported by the National Natural Science Foundation of China(51405499)
文摘A decision support system, including a multi-objective optimization framework and a multi-attribute decision making approach is proposed for satellite equipment layout. Firstly, given three objectives (to minimize the C.G. offset, the cross moments of inertia and the space debris impact risk), we develop a threedimensional layout optimization model. Unlike most of the previous works just focusing on mass characteristics of the system, a space debris impact risk index is developed. Secondly, we develop an efficient optimization framework for the integration of computer-aided design (CAD) software as well as the optimization algorithm to obtain the Pareto front of the layout optimization problem. Thirdly, after obtaining the candidate solutions, we present a multi-attribute decision making approach, which integrates the smart Pareto filter and the correlation coefficient and standard deviation (CCSD) method to select the best tradeoff solutions on the optimal Pareto fronts. Finally, the framework and the decision making approach are applied to a case study of a satellite platform.
基金the National Natural Science Foundations of China (60873099 )
文摘A fuzzy particle swarm optimization （PSO） on the basis of elite archiving is proposed for solving multi-objective optimization problems. First, a new perturbation operator is designed, and the concepts of fuzzy global best and fuzzy personal best are given on basis of the new operator. After that, particle updating equations are revised on the basis of the two new concepts to discourage the premature convergence and enlarge the potential search space; second, the elite archiving technique is used during the process of evolution, namely, the elite particles are introduced into the swarm, whereas the inferior particles are deleted. Therefore, the quality of the swarm is ensured. Finally, the convergence of this swarm is proved. The experimental results show that the nondominated solutions found by the proposed algorithm are uniformly distributed and widely spread along the Pareto front.
基金Project(62073342)supported by the National Natural Science Foundation of ChinaProject(2014 AA 041803)supported by the Hi-tech Research and Development Program of China。
文摘The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previously,they were set by the technical workers according to the offline analysis results and an empirical formula,which leads to unstable process indices and high consumption frequently.So,a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives,where the key technical indices are predicted based on the digestion kinetics of diaspore.A multi-objective state transition algorithm(MOSTA)is improved to solve the problem,in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm.Then a rule based strategy is designed to make the final decision from the Pareto frontiers.The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production.Results show that the proposed method can achieve the technical target while reducing the energy consumption.
基金supported by the National Natural Science Foundation of China(61601505)the Aeronautical Science Foundation of China(20155196022)the Shaanxi Natural Science Foundation of China(2016JQ6050)
文摘To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov process, so that the air combat situation can be effectively calculated via Bayesian inference theory. According to the situation assessment result,adaptively adjusts the weights of maneuver decision factors, which makes the objective function more reasonable and ensures the superiority situation for UCAV. As the air combat game is characterized by highly dynamic and a significant amount of uncertainty,to enhance the robustness and effectiveness of maneuver decision results, fuzzy logic is used to build the functions of four maneuver decision factors. Accuracy prediction of opponent aircraft is also essential to ensure making a good decision; therefore, a prediction model of opponent aircraft is designed based on the elementary maneuver method. Finally, the moving horizon optimization strategy is used to effectively model the whole air combat maneuver decision process. Various simulations are performed on typical scenario test and close-in dogfight, the results sufficiently demonstrate the superiority of the designed maneuver decision method.
文摘To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.
文摘This paper puts forward a new integrated design met ho d based on fuzzy matter-element optimization.On the based of analyzing the mod el of multi-objective fuzzy matter-element , the paper defines the m atter-element weightily and changes solving multi-objective fuzzy optimization into solving dependent function K(x) of the single-objective optimization according to the optimization criterion. The paper particularly describes the realization approach of GA process of multi -objective fuzzy matter-element optimization: encode, produce initial populati on, confirm fitness function, select operator, etc. In the process, the adaptive macro genetic algorithms (AMGA) is applied to enhancing the evolution speed. Th e paper improves the two genetic operators: crossover and mutation operator. The modified adaptive macro genetic algorithms (MAMGA) is put forward simultane ously. It is adopted to solve the optimization problem. Three optimization methods, namely fuzzy matter-element optimization method, li nearity weighted method and fuzzy optimization method, are compared by using the table and figure, it shows that not only MAMGA is a little better than the AMGA , but also it reaches the extent to which the effective iteration generation is 62.2% of simple genetic algorithms (SGA). By the calculation of optimum exam ple, the improved method of genetic in the paper is much better than the method in reference of paper.
文摘This paper presents a fuzzy sequential optimization method for the antenna structures with multiple objectives (structural displacement, weight, cost, nature frequency characteristic) based on fuzzy sets. This has led to a set of new concepts which are discussed here. The paper establishes a sequential optimization model, in which the cost function is constructed, the membership function of single objective is defined as extended quadratic function, the membership function in decision making is constructed with linearly weighted and power product weighted models and the objectives are classed. In addition, the paper presents two methods, namely the linear extended method and the secondary constrained sequential optimization method, by which effective satisfactory design can be found. A computer program is given, optimization computing of the truss- type and antenna structures are described. It is shown that the method is practical and effective.
文摘Predictive control has recently received much attention from researchers. However a challenging problem to be solved is how to tune the parameters of the predictive controller. So far, only few guidelines related to tuning of the parameters of predictive controllers have been provided in literature. In practice, these parameters are generally off-line determined by the designers' experience. From the point of view of process control, it is difficult to find out the optimal parameters for the control system based on a single quadratic performance index, which is used in the standard predictive control algorithm. The fuzzy decision-making function is investigated in this paper. Firstly, M control actions are achieved by unconstrained predictive control algorithm, and fuzzy goals and fuzzy constraints are then calculated and the global satisfaction degree is obtained by fuzzy inference. Moreover, the weighting coefficient λ in the cost function is tuned using simulation optimization according to the fuzzy criteria.
文摘针对未来月面着陆动力下降段轨迹规划需综合考虑多性能指标的问题,提出一种对飞行轨迹先优化后决策的多目标轨迹规划方法.在多目标进化算法MOEA/D-AWA(multi-objective evolutionary algorithm based on decomposition with adaptive weight adjustment)的框架下对轨迹规划的多个指标进行分解,得到若干个单指标的子问题.将凸优化算法作为求解单目标轨迹优化子问题的底层算法,嵌套在MOEA/D-AWA的框架中,经过迭代优化获得一组动力下降段飞行轨迹,其构成多目标轨迹规划问题的帕累托最优解集.根据模糊决策理论对各个帕累托最优解对应的多个轨迹指标逐步降阶并进行综合评估,经过决策得到多指标约束下的飞行轨迹.仿真实验表明,该轨迹规划方法能够在综合多目标的情况下,优化获得一组动力下降轨迹集合,且能够根据不同任务要求从中决策出最优的动力下降段轨迹,可有效解决月面飞行器的多目标轨迹规划问题.
文摘为了解决在实际决策时,由于知识背景不同决策者采用不同粒度语言术语集来表达而导致决策结果不准确的问题,本文提出了一种基于多粒度犹豫模糊语言术语集的逼近理想解排序(technique for order preference by similarity to ideal solution,TOPSIS)决策方法。首先选用各术语集中的最大粒度作为标准粒度,通过转换算法将每个决策者的语言术语集转换到同一标准粒度下进行集结,得出相应的隶属度语言术语集;然后结合TOPSIS方法,计算每个备选方案与正、负理想点距离,以相对贴近度的大小排序实现最优方案的选择;最后,通过一个实例,验证该方法的可行性和优越性。本文所提方法可应用于最优方案的选择问题中,提升决策结果准确度。
