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
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
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
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
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
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
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.
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.
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.
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.
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.
