In this paper, a new approach for generating all or partly efficient solutions called the Combined Approach is developed. The property of efficient solutions generated by the combined approach and its relationships wi...In this paper, a new approach for generating all or partly efficient solutions called the Combined Approach is developed. The property of efficient solutions generated by the combined approach and its relationships with other four approaches: weighting approach, sequential approach, ε-constraint approach and hybrid approach, are discussed. Based on this combined approach, a decision-making support method called the Combined Decision-Making Method (CDMM) for multiobjective problems is developed, which is an interactive process with the decision maker. Only the aspiration levels, which reflect the decision maker's satisfying degrees for corresponding objectives, are needed to be supplied by the decision maker step by step as he will. This interactive way for objectives can easily be accepted. Finally, the application of the proposed decision making method in the resource allocation problem is discussed, and an example for the production decision analysis of the solar energy cells given.展开更多
Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the b...Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the best qualities. A complex multiobjective RA is addressed, and a multiobjective mathematical model is used to find solutions efficiently. Then, all improved particie swarm algorithm （mO_PSO） is proposed combined with a new particle diversity controller policies and dissipation operation. Meanwhile, a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented. The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.展开更多
An application of the multiobjective fault detection and isolation（FDI） approach to an air-breathing hypersonic vehicle（HSV） longitudinal dynamics subject to disturbances is presented.Maintaining sustainable and s...An application of the multiobjective fault detection and isolation（FDI） approach to an air-breathing hypersonic vehicle（HSV） longitudinal dynamics subject to disturbances is presented.Maintaining sustainable and safe flight of HSV is a challenging task due to its strong coupling effects,variable operating conditions and possible failures of system components.A common type of system faults for aircraft including HSV is the loss of effectiveness of its actuators and sensors.To detect and isolate multiple actuator/sensor failures,a faulty linear parameter-varying（LPV） model of HSV is derived by converting actuator/system component faults into equivalent sensor faults.Then a bank of LPV FDI observers is designed to track individual fault with minimum error and suppress the effects of disturbances and other fault signals.The simulation results based on the nonlinear flexible HSV model and a nominal LPV controller demonstrate the effectiveness of the fault estimation technique for HSV.展开更多
With the development of the monitoring technology,it is more and more common that the system is continuously monitored.Therefore,the research on the maintenance optimization of the continuously monitored deterioration...With the development of the monitoring technology,it is more and more common that the system is continuously monitored.Therefore,the research on the maintenance optimization of the continuously monitored deterioration system is important.The deterioration process of the discussed system is described by a Gamma process.The predictive maintenance is considered to be imperfect and formulated.The expected interval of two continuous preventive maintenances is derived.Then,the maintenance optimization model of the continuously monitored deterioration system is presented.In the model,the minimization of the expected operational cost per unit time and the maximization of the system availability are the optimization objectives.The improved ideal point method with the normalized objective functions is employed to solve the proposed model.The validity and sensitivity of the proposed multiobjective maintenance optimization model are analyzed by a numerical example.展开更多
The multiobjective group decision-making problem under risk is common in reality. This paper focuses on the study about risky multiobjective group decision-making problem where the index value is not certain. We give ...The multiobjective group decision-making problem under risk is common in reality. This paper focuses on the study about risky multiobjective group decision-making problem where the index value is not certain. We give indexes classifying method and index normalizing formula of this type problem. By building objective function that minimizes general weighted distance from every alternative to the relatively best and worst alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, and by building another objective function that minimizes general weighted distance from the optimal membership degree of every decision-maker to every alternative to the group optimal alternative and the group inferior alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, which are both based on probability theory and fuzzy theory. Aftermost a model is established which collects group preferences. This method provides a new idea and approach for solving multiobjective decision-making problem among uncertain system, which is applicable for practical problem. Finally a case study shows a satisfactory result.展开更多
In view of two-level multiobjective decision making problem, and employing satisfactoriness of objective function and trade-off rate between objective functions, an interactive two-level multiobjective decision making...In view of two-level multiobjective decision making problem, and employing satisfactoriness of objective function and trade-off rate between objective functions, an interactive two-level multiobjective decision making method is proposed in this paper. By using the method, the obtained solution can be acceptable to both the follower and the requirement of the leader. It's an efficient method to solve two-level multiobjective decision making problems.展开更多
实数编码的多目标进化算法常使用模拟二进制交叉(simulated binary crossover,称SBX)算子.通过对SBX以及进化策略中变异算子进行对比分析,并引入进化策略中的离散重组算子,提出了一种正态分布交叉(normal distribution crossover,称NDX...实数编码的多目标进化算法常使用模拟二进制交叉(simulated binary crossover,称SBX)算子.通过对SBX以及进化策略中变异算子进行对比分析,并引入进化策略中的离散重组算子,提出了一种正态分布交叉(normal distribution crossover,称NDX)算子.首先在一维搜索空间实例中对NDX与SBX算子进行比较和分析,然后将NDX算子应用于Deb等人提出的稳态多目标进化算法ε-MOEA(ε-dominance based multiobjective evolutionary algorithm)中.采用NDX算子的ε-MOEA(记为ε-MOEA/NDX)算法在多目标优化标准测试集ZDT和DTLZ的10个函数上进行了实验比较.实验结果和分析表明,采用NDX的ε-MOEA所求得的Pareto最优解集质量明显优于经典算法ε-MOEA/SBX和NSGA-Ⅱ.展开更多
This paper presents a path planning approach for rotary unmanned aerial vehicles(R-UAVs)in a known static rough terrain environment.This approach aims to find collision-free and feasible paths with minimum altitude,le...This paper presents a path planning approach for rotary unmanned aerial vehicles(R-UAVs)in a known static rough terrain environment.This approach aims to find collision-free and feasible paths with minimum altitude,length and angle variable rate.First,a three-dimensional(3D)modeling method is proposed to reduce the computation burden of the dynamic models of R-UAVs.Considering the length,height and tuning angle of a path,the path planning of R-UAVs is described as a tri-objective optimization problem.Then,an improved multi-objective particle swarm optimization algorithm is developed.To render the algorithm more effective in dealing with this problem,a vibration function is introduced into the collided solutions to improve the algorithm efficiency.Meanwhile,the selection of the global best position is taken into account by the reference point method.Finally,the experimental environment is built with the help of the Google map and the 3D terrain generator World Machine.Experimental results under two different rough terrains from Guilin and Lanzhou of China demonstrate the capabilities of the proposed algorithm in finding Pareto optimal paths.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
Quality of service (QoS) multicast routing has continued to be a very important research topic in the Internet. A method of multicast routing is proposed to simultaneously optimize several parameters based on multiobj...Quality of service (QoS) multicast routing has continued to be a very important research topic in the Internet. A method of multicast routing is proposed to simultaneously optimize several parameters based on multiobjective genetic algorithm, after the related work is reviewed. The contribution lies on that the selection process of such routing is treated with multiobjective optimization. Different quality criterions in IP network are taken into account for multicast communications. A set of routing trees is generated to approximate the Pareto front of multicast problem. Multiple trees can be selected from the final set of nondominated solutions, and applied to obtain a good overall link cost and balance traffic distribution according to some simulation results.展开更多
文摘In this paper, a new approach for generating all or partly efficient solutions called the Combined Approach is developed. The property of efficient solutions generated by the combined approach and its relationships with other four approaches: weighting approach, sequential approach, ε-constraint approach and hybrid approach, are discussed. Based on this combined approach, a decision-making support method called the Combined Decision-Making Method (CDMM) for multiobjective problems is developed, which is an interactive process with the decision maker. Only the aspiration levels, which reflect the decision maker's satisfying degrees for corresponding objectives, are needed to be supplied by the decision maker step by step as he will. This interactive way for objectives can easily be accepted. Finally, the application of the proposed decision making method in the resource allocation problem is discussed, and an example for the production decision analysis of the solar energy cells given.
基金the National Natural Science Foundation of China (60573159)
文摘Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the best qualities. A complex multiobjective RA is addressed, and a multiobjective mathematical model is used to find solutions efficiently. Then, all improved particie swarm algorithm （mO_PSO） is proposed combined with a new particle diversity controller policies and dissipation operation. Meanwhile, a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented. The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.
文摘An application of the multiobjective fault detection and isolation（FDI） approach to an air-breathing hypersonic vehicle（HSV） longitudinal dynamics subject to disturbances is presented.Maintaining sustainable and safe flight of HSV is a challenging task due to its strong coupling effects,variable operating conditions and possible failures of system components.A common type of system faults for aircraft including HSV is the loss of effectiveness of its actuators and sensors.To detect and isolate multiple actuator/sensor failures,a faulty linear parameter-varying（LPV） model of HSV is derived by converting actuator/system component faults into equivalent sensor faults.Then a bank of LPV FDI observers is designed to track individual fault with minimum error and suppress the effects of disturbances and other fault signals.The simulation results based on the nonlinear flexible HSV model and a nominal LPV controller demonstrate the effectiveness of the fault estimation technique for HSV.
基金supported by the Fundamental Research Funds for the Central Universities (N090303005)Key National Science and Technology Special Project (2010ZX04014-014)
文摘With the development of the monitoring technology,it is more and more common that the system is continuously monitored.Therefore,the research on the maintenance optimization of the continuously monitored deterioration system is important.The deterioration process of the discussed system is described by a Gamma process.The predictive maintenance is considered to be imperfect and formulated.The expected interval of two continuous preventive maintenances is derived.Then,the maintenance optimization model of the continuously monitored deterioration system is presented.In the model,the minimization of the expected operational cost per unit time and the maximization of the system availability are the optimization objectives.The improved ideal point method with the normalized objective functions is employed to solve the proposed model.The validity and sensitivity of the proposed multiobjective maintenance optimization model are analyzed by a numerical example.
文摘The multiobjective group decision-making problem under risk is common in reality. This paper focuses on the study about risky multiobjective group decision-making problem where the index value is not certain. We give indexes classifying method and index normalizing formula of this type problem. By building objective function that minimizes general weighted distance from every alternative to the relatively best and worst alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, and by building another objective function that minimizes general weighted distance from the optimal membership degree of every decision-maker to every alternative to the group optimal alternative and the group inferior alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, which are both based on probability theory and fuzzy theory. Aftermost a model is established which collects group preferences. This method provides a new idea and approach for solving multiobjective decision-making problem among uncertain system, which is applicable for practical problem. Finally a case study shows a satisfactory result.
文摘In view of two-level multiobjective decision making problem, and employing satisfactoriness of objective function and trade-off rate between objective functions, an interactive two-level multiobjective decision making method is proposed in this paper. By using the method, the obtained solution can be acceptable to both the follower and the requirement of the leader. It's an efficient method to solve two-level multiobjective decision making problems.
文摘实数编码的多目标进化算法常使用模拟二进制交叉(simulated binary crossover,称SBX)算子.通过对SBX以及进化策略中变异算子进行对比分析,并引入进化策略中的离散重组算子,提出了一种正态分布交叉(normal distribution crossover,称NDX)算子.首先在一维搜索空间实例中对NDX与SBX算子进行比较和分析,然后将NDX算子应用于Deb等人提出的稳态多目标进化算法ε-MOEA(ε-dominance based multiobjective evolutionary algorithm)中.采用NDX算子的ε-MOEA(记为ε-MOEA/NDX)算法在多目标优化标准测试集ZDT和DTLZ的10个函数上进行了实验比较.实验结果和分析表明,采用NDX的ε-MOEA所求得的Pareto最优解集质量明显优于经典算法ε-MOEA/SBX和NSGA-Ⅱ.
基金supported by the National Natural Science Foundation of China(6167321461673217+2 种基金61673219)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(18KJB120011)the Postgraduate Research and Practice Innovation Program of Jiangsu Province(KYCX19_0299)
文摘This paper presents a path planning approach for rotary unmanned aerial vehicles(R-UAVs)in a known static rough terrain environment.This approach aims to find collision-free and feasible paths with minimum altitude,length and angle variable rate.First,a three-dimensional(3D)modeling method is proposed to reduce the computation burden of the dynamic models of R-UAVs.Considering the length,height and tuning angle of a path,the path planning of R-UAVs is described as a tri-objective optimization problem.Then,an improved multi-objective particle swarm optimization algorithm is developed.To render the algorithm more effective in dealing with this problem,a vibration function is introduced into the collided solutions to improve the algorithm efficiency.Meanwhile,the selection of the global best position is taken into account by the reference point method.Finally,the experimental environment is built with the help of the Google map and the 3D terrain generator World Machine.Experimental results under two different rough terrains from Guilin and Lanzhou of China demonstrate the capabilities of the proposed algorithm in finding Pareto optimal paths.
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Quality of service (QoS) multicast routing has continued to be a very important research topic in the Internet. A method of multicast routing is proposed to simultaneously optimize several parameters based on multiobjective genetic algorithm, after the related work is reviewed. The contribution lies on that the selection process of such routing is treated with multiobjective optimization. Different quality criterions in IP network are taken into account for multicast communications. A set of routing trees is generated to approximate the Pareto front of multicast problem. Multiple trees can be selected from the final set of nondominated solutions, and applied to obtain a good overall link cost and balance traffic distribution according to some simulation results.
