The dynamic optimal interpolation(DOI)method is a technique based on quasi-geostrophic dynamics for merging multi-satellite altimeter along-track observations to generate gridded absolute dynamic topography(ADT).Compa...The dynamic optimal interpolation(DOI)method is a technique based on quasi-geostrophic dynamics for merging multi-satellite altimeter along-track observations to generate gridded absolute dynamic topography(ADT).Compared with the linear optimal interpolation(LOI)method,the DOI method can improve the accuracy of gridded ADT locally but with low computational efficiency.Consequently,considering both computational efficiency and accuracy,the DOI method is more suitable to be used only for regional applications.In this study,we propose to evaluate the suitable region for applying the DOI method based on the correlation between the absolute value of the Jacobian operator of the geostrophic stream function and the improvement achieved by the DOI method.After verifying the LOI and DOI methods,the suitable region was investigated in three typical areas:the Gulf Stream(25°N-50°N,55°W-80°W),the Japanese Kuroshio(25°N-45°N,135°E-155°E),and the South China Sea(5°N-25°N,100°E-125°E).We propose to use the DOI method only in regions outside the equatorial region and where the absolute value of the Jacobian operator of the geostrophic stream function is higher than1×10^(-11).展开更多
In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic op...In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic optimization. This method includes two steps of optimization, that is, kinematic and dynamic optimization. Meanwhile, it uses the results of the kinematic optimization as the constraint equations of dynamic optimization. This method is used in the parameters optimization of transplanting mechanism with elliptic planetary gears of high-speed rice seedling transplanter with remarkable significance. The parameters spectrum, which meets to the kinematic requirements, is obtained through visualized human-computer interactions in the kinematics optimization, and the optimal parameters are obtained based on improved genetic algorithm in dynamic optimization. In the dynamic optimization, the objective function is chosen as the optimal' dynamic behavior and the constraint equations are from the results of the kinematic optimization, This method is suitable for multi-objective optimization when both the kinematic and dynamic performances act as objective functions.展开更多
Rolling stock manufacturers are finding structural solutions to reduce power required by the vehicles,and the lightweight design of the car body represents a possible solution.Optimization processes and innovative mat...Rolling stock manufacturers are finding structural solutions to reduce power required by the vehicles,and the lightweight design of the car body represents a possible solution.Optimization processes and innovative materials can be combined in order to achieve this goal.In this framework,we propose the redesign and optimization process of the car body roof for a light rail vehicle,introducing a sandwich structure.Bonded joint was used as a fastening system.The project was carried out on a single car of a modern tram platform.This preliminary numerical work was developed in two main steps:redesign of the car body structure and optimization of the innovated system.Objective of the process was the mass reduction of the whole metallic structure,while the constraint condition was imposed on the first frequency of vibration of the system.The effect of introducing a sandwich panel within the roof assembly was evaluated,focusing on the mechanical and dynamic performances of the whole car body.A mass saving of 63%on the optimized components was achieved,corresponding to a 7.6%if compared to the complete car body shell.In addition,a positive increasing of 17.7%on the first frequency of vibration was observed.Encouraging results have been achieved in terms of weight reduction and mechanical behaviour of the innovated car body.展开更多
Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time.In such problems,it is commonly assumed that all problem instances are feasible.In r...Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time.In such problems,it is commonly assumed that all problem instances are feasible.In reality some instances can be infeasible due to various practical issues,such as a sudden change in resource requirements or a big change in the availability of resources.Decision-makers have to determine whether a particular instance is feasible or not,as infeasible instances cannot be solved as there are no solutions to implement.In this case,locating the nearest feasible solution would be valuable information for the decision-makers.In this paper,a differential evolution algorithm is proposed for solving dynamic constrained problems that learns from past environments and transfers important knowledge from them to use in solving the current instance and includes a mechanism for suggesting a good feasible solution when an instance is infeasible.To judge the performance of the proposed algorithm,13 well-known dynamic test problems were solved.The results indicate that the proposed algorithm outperforms existing recent algorithms with a margin of 79.40%over all the environments and it can also find a good,but infeasible solution,when an instance is infeasible.展开更多
As the scale of power networks has expanded,the demand for multi-service transmission has gradually increased.The emergence of WiFi6 has improved the transmission efficiency and resource utilization of wireless networ...As the scale of power networks has expanded,the demand for multi-service transmission has gradually increased.The emergence of WiFi6 has improved the transmission efficiency and resource utilization of wireless networks.However,it still cannot cope with situations such as wireless access point(AP)failure.To solve this problem,this paper combines orthogonal fre-quency division multiple access(OFDMA)technology and dynamic channel optimization technology to design a fault-tolerant WiFi6 dynamic resource optimization method for achieving high quality wireless services in a wirelessly covered network even when an AP fails.First,under the premise of AP layout with strong coverage over the whole area,a faulty AP determination method based on beacon frames(BF)is designed.Then,the maximum signal-to-interference ratio(SINR)is used as the principle to select AP reconnection for the affected users.Finally,this paper designs a dynamic access selection model(DASM)for service frames of power Internet of Things(IoTs)and a schedul-ing access optimization model(SAO-MF)based on multi-frame transmission,which enables access optimization for differentiated services.For the above mechanisms,a heuristic resource allocation algorithm is proposed in SAO-MF.Simulation results show that the method can reduce the delay by 15%and improve the throughput by 55%,ensuring high-quality communication in power wireless networks.展开更多
A smooth bidirectional evolutionary structural optimization(SBESO),as a bidirectional version of SESO is proposed to solve the topological optimization of vibrating continuum structures for natural frequencies and dyn...A smooth bidirectional evolutionary structural optimization(SBESO),as a bidirectional version of SESO is proposed to solve the topological optimization of vibrating continuum structures for natural frequencies and dynamic compliance under the transient load.A weighted function is introduced to regulate the mass and stiffness matrix of an element,which has the inefficient element gradually removed from the design domain as if it were undergoing damage.Aiming at maximizing the natural frequency of a structure,the frequency optimization formulation is proposed using the SBESO technique.The effects of various weight functions including constant,linear and sine functions on structural optimization are compared.With the equivalent static load(ESL)method,the dynamic stiffness optimization of a structure is formulated by the SBESO technique.Numerical examples show that compared with the classic BESO method,the SBESO method can efficiently suppress the excessive element deletion by adjusting the element deletion rate and weight function.It is also found that the proposed SBESO technique can obtain an efficient configuration and smooth boundary and demonstrate the advantages over the classic BESO technique.展开更多
Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the ...Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the goal is no longer to search for the optimal solution(s) of a fixed problem but to track the moving optimum over time. Dynamic optimization problems have attracted a growing interest from the genetic algorithm community in recent years. Several approaches have been developed to enhance the performance of genetic algorithms in dynamic environments. One approach is to maintain the diversity of the population via random immigrants. This paper proposes a hybrid immigrants scheme that combines the concepts of elitism, dualism and random immigrants for genetic algorithms to address dynamic optimization problems. In this hybrid scheme, the best individual, i.e., the elite, from the previous generation and its dual individual are retrieved as the bases to create immigrants via traditional mutation scheme. These elitism-based and dualism-based immigrants together with some random immigrants are substituted into the current population, replacing the worst individuals in the population. These three kinds of immigrants aim to address environmental changes of slight, medium and significant degrees respectively and hence efficiently adapt genetic algorithms to dynamic environments that are subject to different severities of changes. Based on a series of systematically constructed dynamic test problems, experiments are carried out to investigate the performance of genetic algorithms with the hybrid immigrants scheme and traditional random immigrants scheme. Experimental results validate the efficiency of the proposed hybrid immigrants scheme for improving the performance of genetic algorithms in dynamic environments.展开更多
The dynamic dexterity is an important issue for manipulator design, some indices were proposed for analyzing dynamic dexterity, but they can evaluate the dynamic performance just at one pose in the workspaee of the ma...The dynamic dexterity is an important issue for manipulator design, some indices were proposed for analyzing dynamic dexterity, but they can evaluate the dynamic performance just at one pose in the workspaee of the manipulator, and can't be applied to dynamic design expediently. Much work has been done in the kinematic optimization, but the work in the dynamic optimization is much less. A global dynamic condition number index is proposed and applied to the dynamic optimization design the parallel manipulator. This paper deals with the dynamic manipulability and dynamic optimization of a two degree-of-freedom (DOF) parallel manipulator. The particular velocity and particular angular velocity matrices of each moving part about the part's pivot point are derived fi'om the kinematic formulation of the manipulator, and the inertial force and inertial movement are obtained utilizing Newton-Euler formulation, then the inverse dynamic model of the parallel manipulator is proposed based on the virtual work principle. The general inertial ellipsoid and dynamic manipulability ellipsoid are applied to evaluate the dynamic performance of the manipulator, a global dynamic condition number index based on the condition number of general inertial matrix in the workspace is proposed, and then the link lengths of the manipulator is redesigned to optimize the dynamic manipulability by this index. The dynamic manipulability of the origin mechanism and the optimized mechanism are compared, the result shows that the optimized one is much better. The global dynamic condition number index has good effect in evaluating the dynamic dexterity of the whole workspace, and is efficient in the dynamic optimal design of the parallel manipulator.展开更多
Dynamic optimization of electromechanical coupling system is a significant engineering problem in the field of mechatronics. The performance improvement of electromechanical equipment depends on the system design para...Dynamic optimization of electromechanical coupling system is a significant engineering problem in the field of mechatronics. The performance improvement of electromechanical equipment depends on the system design parameters. Aiming at the spindle unit of refitted machine tool for solid rocket, the vibration acceleration of tool is taken as objective function, and the electromechanical system design parameters are appointed as design variables. Dynamic optimization model is set up by adopting Lagrange-Maxwell equations, Park transform and electromechanical system energy equations. In the procedure of seeking high efficient optimization method, exponential function is adopted to be the weight function of particle swarm optimization algorithm. Exponential inertia weight particle swarm algorithm(EPSA), is formed and applied to solve the dynamic optimization problem of electromechanical system. The probability density function of EPSA is presented and used to perform convergence analysis. After calculation, the optimized design parameters of the spindle unit are obtained in limited time period. The vibration acceleration of the tool has been decreased greatly by the optimized design parameters. The research job in the paper reveals that the problem of dynamic optimization of electromechanical system can be solved by the method of combining system dynamic analysis with reformed swarm particle optimizati on. Such kind of method can be applied in the design of robots, NC machine, and other electromechanical equipments.展开更多
In dynamic environments,it is important to track changing optimal solutions over time.Univariate marginal distribution algorithm(UMDA) which is a class algorithm of estimation of distribution algorithms attracts mor...In dynamic environments,it is important to track changing optimal solutions over time.Univariate marginal distribution algorithm(UMDA) which is a class algorithm of estimation of distribution algorithms attracts more and more attention in recent years.In this paper a new multi-population and diffusion UMDA(MDUMDA) is proposed for dynamic multimodal problems.The multi-population approach is used to locate multiple local optima which are useful to find the global optimal solution quickly to dynamic multimodal problems.The diffusion model is used to increase the diversity in a guided fashion,which makes the neighbor individuals of previous optimal solutions move gradually from the previous optimal solutions and enlarge the search space.This approach uses both the information of current population and the part history information of the optimal solutions.Finally experimental studies on the moving peaks benchmark are carried out to evaluate the proposed algorithm and compare the performance of MDUMDA and multi-population quantum swarm optimization(MQSO) from the literature.The experimental results show that the MDUMDA is effective for the function with moving optimum and can adapt to the dynamic environments rapidly.展开更多
Work on dynamic topology optimization of engineering structures for vibration suppression has mainly addressed the maximization of eigenfrequencies and gaps between consecutive eigenfrequencies of free vibration, mini...Work on dynamic topology optimization of engineering structures for vibration suppression has mainly addressed the maximization of eigenfrequencies and gaps between consecutive eigenfrequencies of free vibration, minimization of the dynamic compliance subject to forced vibration, and minimization of the structural frequency response. A dynamic topology optimization method of bi-material plate structures is presented based on power flow analysis. Topology optimization problems formulated directly with the design objective of minimizing the power flow response are dealt with. In comparison to the displacement or velocity response, the power flow response takes not only the amplitude of force and velocity into account, but also the phase relationship of the two vector quantities. The complex expression of power flow response is derived based on time-harmonic external mechanical loading and Rayleigh damping. The mathematical formulation of topology optimization is established based on power flow response and bi-material solid isotropic material with penalization(SIMP) model. Computational optimization procedure is developed by using adjoint design sensitivity analysis and the method of moving asymptotes(MMA). Several numerical examples are presented for bi-material plate structures with different loading frequencies, which verify the feasibility and effectiveness of this method. Additionally, optimum results between topological design of minimum power flow response and minimum dynamic compliance are compared, showing that the present method has strong adaptability for structural dynamic topology optimization problems. The proposed research provides a more accurate and effective approach for dynamic topology optimization of vibrating structures.展开更多
A new method to solve dynamic nonlinear constrained optimization problems (DNCOP) is proposed. First, the time (environment) variable period of DNCOP is divided into several equal subperiods. In each subperiod, th...A new method to solve dynamic nonlinear constrained optimization problems (DNCOP) is proposed. First, the time (environment) variable period of DNCOP is divided into several equal subperiods. In each subperiod, the DNCOP is approximated by a static nonlinear constrained optimization problem (SNCOP). Second, for each SNCOP, inspired by the idea of multiobjective optimization, it is transformed into a static bi-objective optimization problem. As a result, the original DNCOP is approximately transformed into several static bi-objective optimization problems. Third, a new multiobjective evolutionary algorithm is proposed based on a new selection operator and an improved nonuniformity mutation operator. The simulation results indicate that the proposed algorithm is effective for DNCOP.展开更多
Decarbonization of the electricity sector is crucial to mitigate the impacts of climate change and global warming over the coming decades.The key challenges for achieving this goal are carbon emission trading and elec...Decarbonization of the electricity sector is crucial to mitigate the impacts of climate change and global warming over the coming decades.The key challenges for achieving this goal are carbon emission trading and electricity sector regulation,which are also the major components of the carbon and electricity markets,respectively.In this paper,a joint electricity and carbon market model is proposed to investigate the relationships between electricity price,carbon price,and electricity generation capacity,thereby identifying pathways toward a renewable energy transition under the transactional energy interconnection framework.The proposed model is a dynamically iterative optimization model consisting of upper-level and lower-level models.The upper-level model optimizes power generation and obtains the electricity price,which drives the lower-level model to update the carbon price and electricity generation capacity.The proposed model is verified using the Northeast Asia power grid.The results show that increasing carbon price will result in increased electricity price,along with further increases in renewable energy generation capacity in the following period.This increase in renewable energy generation will reduce reliance on carbon-emitting energy sources,and hence the carbon price will decline.Moreover,the interconnection among zones in the Northeast Asia power grid will enable reasonable allocation of zonal power generation.Carbon capture and storage (CCS) will be an effective technology to reduce the carbon emissions and further realize the emission reduction targets in 2030-2050.It eases the stress of realizing the energy transition because of the less urgency to install additional renewable energy capacity.展开更多
Associated dynamic performance of the clamping force control valve used in continuously variable transmission (CVT) is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dy...Associated dynamic performance of the clamping force control valve used in continuously variable transmission (CVT) is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dynamic model is set up by means of mechanism analysis. For the purpose of checking the validity of the modeling method, a prototype workpiece of the valve is manufactured for comparison test, and its simulation result follows the experimental result quite well. An associated performance index is founded considering the response time, overshoot and saving energy, and five structural parameters are selected to adjust for deriving the optimal associated performance index. The optimization problem is solved by the genetic algorithm (GA) with necessary constraints. Finally, the properties of the optimized valve are compared with those of the prototype workpiece, and the results prove that the dynamic performance indexes of the optimized valve are much better than those of the prototype workpiece.展开更多
A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation (DISOPE) was proposed for nonlinear cascade systems under network environment. Under the d...A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation (DISOPE) was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.展开更多
This paper first introduces the technical requirements for autonomous flight, with a brief review of the International Academy of Astronautics(IAA) study group, "autonomous dynamic trajectory optimization control...This paper first introduces the technical requirements for autonomous flight, with a brief review of the International Academy of Astronautics(IAA) study group, "autonomous dynamic trajectory optimization control of launch vehicle". Two research scenarios, ascent rescue and powered descent, are compared from the viewpoint of optimal control. On this basis, the technologies on the autonomous trajectory planning and control under the thrust-drop failures in the ascending phase, and the autonomous guidance method during the powered landing for the recovery of the rockets are discussed respectively. For the ascending problem, the characteristics of different solutions, including the iterative guidance method(IGM)-based residual carrying capacity evaluation, the state-triggered indices(STI), the joint planning with the payload’s performance, and the multiple graded optimization(MGO), are analyzed for comparison. For the landing problem, the challenges such as the feasible region reduction caused by high thrust weight ratio(HTWR) and the disturbance adaptability brought by the limited feasible region, are studied in detail, as well as the onboard planning demonstration flight in China are introduced. Finally, the foundations supporting the above methods are summarized, which play an important role in promoting the flight autonomy.展开更多
In this paper, a minimax design of damped dynamic vibration absorber for a damped primary system is investigated to minimize the vibration magnitude peaks. Moreover, to reduce the sensitivity of the primary system res...In this paper, a minimax design of damped dynamic vibration absorber for a damped primary system is investigated to minimize the vibration magnitude peaks. Moreover, to reduce the sensitivity of the primary system response to variations of the forcing frequency for a two- degree-of-freedom system, the primary system should have two equal resonance magnitude peaks. To meet this re- quirement, a set of simplified constraint equations includ- ing distribution characteristics of the resonant frequencies of the primary system is established for the minimax objective function. The modified constraint equations have less un- known variables than those by other authors, which not only simplifies the computation but also improves the accuracy of the optimal values. The advantage of the proposed method is illustrated through numerical simulations.展开更多
Time and space complexity is themost critical problemof the current routing optimization algorithms for Software Defined Networking(SDN).To overcome this complexity,researchers use meta-heuristic techniques inside the...Time and space complexity is themost critical problemof the current routing optimization algorithms for Software Defined Networking(SDN).To overcome this complexity,researchers use meta-heuristic techniques inside the routing optimization algorithms in the OpenFlow(OF)based large scale SDNs.This paper proposes a hybrid meta-heuristic algorithm to optimize the dynamic routing problem for the large scale SDNs.Due to the dynamic nature of SDNs,the proposed algorithm uses amutation operator to overcome the memory-based problem of the ant colony algorithm.Besides,it uses the box-covering method and the k-means clustering method to divide the SDN network to overcome the problemof time and space complexity.The results of the proposed algorithm compared with the results of other similar algorithms and it shows that the proposed algorithm can handle the dynamic network changing,reduce the network congestion,the delay and running times and the packet loss rates.展开更多
Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily appli...Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.展开更多
Cooperative path dynamic planning of a UCAV (unmanned combat air vehicle) team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among member...Cooperative path dynamic planning of a UCAV (unmanned combat air vehicle) team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.展开更多
基金supported by National Natural Science Foundation of China under Grants 42192531 and 42192534the Special Fund of Hubei Luojia Laboratory(China)under Grant 220100001the Natural Science Foundation of Hubei Province for Distinguished Young Scholars(China)under Grant 2022CFA090。
文摘The dynamic optimal interpolation(DOI)method is a technique based on quasi-geostrophic dynamics for merging multi-satellite altimeter along-track observations to generate gridded absolute dynamic topography(ADT).Compared with the linear optimal interpolation(LOI)method,the DOI method can improve the accuracy of gridded ADT locally but with low computational efficiency.Consequently,considering both computational efficiency and accuracy,the DOI method is more suitable to be used only for regional applications.In this study,we propose to evaluate the suitable region for applying the DOI method based on the correlation between the absolute value of the Jacobian operator of the geostrophic stream function and the improvement achieved by the DOI method.After verifying the LOI and DOI methods,the suitable region was investigated in three typical areas:the Gulf Stream(25°N-50°N,55°W-80°W),the Japanese Kuroshio(25°N-45°N,135°E-155°E),and the South China Sea(5°N-25°N,100°E-125°E).We propose to use the DOI method only in regions outside the equatorial region and where the absolute value of the Jacobian operator of the geostrophic stream function is higher than1×10^(-11).
基金This project is supported by National Natural Science Foundation of China (No.50275137)Basic Research Major Project of China Science and Technology Ministry(No.2004CCA05700)Provincial Natural Science Foundation of Zhejiang, China (No. Z105706).
文摘In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic optimization. This method includes two steps of optimization, that is, kinematic and dynamic optimization. Meanwhile, it uses the results of the kinematic optimization as the constraint equations of dynamic optimization. This method is used in the parameters optimization of transplanting mechanism with elliptic planetary gears of high-speed rice seedling transplanter with remarkable significance. The parameters spectrum, which meets to the kinematic requirements, is obtained through visualized human-computer interactions in the kinematics optimization, and the optimal parameters are obtained based on improved genetic algorithm in dynamic optimization. In the dynamic optimization, the objective function is chosen as the optimal' dynamic behavior and the constraint equations are from the results of the kinematic optimization, This method is suitable for multi-objective optimization when both the kinematic and dynamic performances act as objective functions.
文摘Rolling stock manufacturers are finding structural solutions to reduce power required by the vehicles,and the lightweight design of the car body represents a possible solution.Optimization processes and innovative materials can be combined in order to achieve this goal.In this framework,we propose the redesign and optimization process of the car body roof for a light rail vehicle,introducing a sandwich structure.Bonded joint was used as a fastening system.The project was carried out on a single car of a modern tram platform.This preliminary numerical work was developed in two main steps:redesign of the car body structure and optimization of the innovated system.Objective of the process was the mass reduction of the whole metallic structure,while the constraint condition was imposed on the first frequency of vibration of the system.The effect of introducing a sandwich panel within the roof assembly was evaluated,focusing on the mechanical and dynamic performances of the whole car body.A mass saving of 63%on the optimized components was achieved,corresponding to a 7.6%if compared to the complete car body shell.In addition,a positive increasing of 17.7%on the first frequency of vibration was observed.Encouraging results have been achieved in terms of weight reduction and mechanical behaviour of the innovated car body.
基金supported by the Australian Research Council Discovery Project(Grant Nos.DP210102939).
文摘Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time.In such problems,it is commonly assumed that all problem instances are feasible.In reality some instances can be infeasible due to various practical issues,such as a sudden change in resource requirements or a big change in the availability of resources.Decision-makers have to determine whether a particular instance is feasible or not,as infeasible instances cannot be solved as there are no solutions to implement.In this case,locating the nearest feasible solution would be valuable information for the decision-makers.In this paper,a differential evolution algorithm is proposed for solving dynamic constrained problems that learns from past environments and transfers important knowledge from them to use in solving the current instance and includes a mechanism for suggesting a good feasible solution when an instance is infeasible.To judge the performance of the proposed algorithm,13 well-known dynamic test problems were solved.The results indicate that the proposed algorithm outperforms existing recent algorithms with a margin of 79.40%over all the environments and it can also find a good,but infeasible solution,when an instance is infeasible.
基金supported by State Grid Jiangsu Electric Power Co.,Ltd.Science and Technology Project“Research on Low-Cost Wireless Coverage and Trusted Access Technologies for Underground Pipe Gallery Digital Network”(J2021081).
文摘As the scale of power networks has expanded,the demand for multi-service transmission has gradually increased.The emergence of WiFi6 has improved the transmission efficiency and resource utilization of wireless networks.However,it still cannot cope with situations such as wireless access point(AP)failure.To solve this problem,this paper combines orthogonal fre-quency division multiple access(OFDMA)technology and dynamic channel optimization technology to design a fault-tolerant WiFi6 dynamic resource optimization method for achieving high quality wireless services in a wirelessly covered network even when an AP fails.First,under the premise of AP layout with strong coverage over the whole area,a faulty AP determination method based on beacon frames(BF)is designed.Then,the maximum signal-to-interference ratio(SINR)is used as the principle to select AP reconnection for the affected users.Finally,this paper designs a dynamic access selection model(DASM)for service frames of power Internet of Things(IoTs)and a schedul-ing access optimization model(SAO-MF)based on multi-frame transmission,which enables access optimization for differentiated services.For the above mechanisms,a heuristic resource allocation algorithm is proposed in SAO-MF.Simulation results show that the method can reduce the delay by 15%and improve the throughput by 55%,ensuring high-quality communication in power wireless networks.
基金supported by the National Natural Science Foundation of China (Grant No.51505096)the Natural Science Foundation of Heilongjiang Province (Grant No.LH2020E064).
文摘A smooth bidirectional evolutionary structural optimization(SBESO),as a bidirectional version of SESO is proposed to solve the topological optimization of vibrating continuum structures for natural frequencies and dynamic compliance under the transient load.A weighted function is introduced to regulate the mass and stiffness matrix of an element,which has the inefficient element gradually removed from the design domain as if it were undergoing damage.Aiming at maximizing the natural frequency of a structure,the frequency optimization formulation is proposed using the SBESO technique.The effects of various weight functions including constant,linear and sine functions on structural optimization are compared.With the equivalent static load(ESL)method,the dynamic stiffness optimization of a structure is formulated by the SBESO technique.Numerical examples show that compared with the classic BESO method,the SBESO method can efficiently suppress the excessive element deletion by adjusting the element deletion rate and weight function.It is also found that the proposed SBESO technique can obtain an efficient configuration and smooth boundary and demonstrate the advantages over the classic BESO technique.
基金This work was supported by UK EPSRC(No.EP/E060722/01)Broil FAPESP(Proc.04/04289-6).
文摘Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the goal is no longer to search for the optimal solution(s) of a fixed problem but to track the moving optimum over time. Dynamic optimization problems have attracted a growing interest from the genetic algorithm community in recent years. Several approaches have been developed to enhance the performance of genetic algorithms in dynamic environments. One approach is to maintain the diversity of the population via random immigrants. This paper proposes a hybrid immigrants scheme that combines the concepts of elitism, dualism and random immigrants for genetic algorithms to address dynamic optimization problems. In this hybrid scheme, the best individual, i.e., the elite, from the previous generation and its dual individual are retrieved as the bases to create immigrants via traditional mutation scheme. These elitism-based and dualism-based immigrants together with some random immigrants are substituted into the current population, replacing the worst individuals in the population. These three kinds of immigrants aim to address environmental changes of slight, medium and significant degrees respectively and hence efficiently adapt genetic algorithms to dynamic environments that are subject to different severities of changes. Based on a series of systematically constructed dynamic test problems, experiments are carried out to investigate the performance of genetic algorithms with the hybrid immigrants scheme and traditional random immigrants scheme. Experimental results validate the efficiency of the proposed hybrid immigrants scheme for improving the performance of genetic algorithms in dynamic environments.
基金supported by National Natural Science Foundation of China (Grant No. 50605041, No. 50775125)National Basic Research Program of China (973 Program, Grant No. 2006CB705400)
文摘The dynamic dexterity is an important issue for manipulator design, some indices were proposed for analyzing dynamic dexterity, but they can evaluate the dynamic performance just at one pose in the workspaee of the manipulator, and can't be applied to dynamic design expediently. Much work has been done in the kinematic optimization, but the work in the dynamic optimization is much less. A global dynamic condition number index is proposed and applied to the dynamic optimization design the parallel manipulator. This paper deals with the dynamic manipulability and dynamic optimization of a two degree-of-freedom (DOF) parallel manipulator. The particular velocity and particular angular velocity matrices of each moving part about the part's pivot point are derived fi'om the kinematic formulation of the manipulator, and the inertial force and inertial movement are obtained utilizing Newton-Euler formulation, then the inverse dynamic model of the parallel manipulator is proposed based on the virtual work principle. The general inertial ellipsoid and dynamic manipulability ellipsoid are applied to evaluate the dynamic performance of the manipulator, a global dynamic condition number index based on the condition number of general inertial matrix in the workspace is proposed, and then the link lengths of the manipulator is redesigned to optimize the dynamic manipulability by this index. The dynamic manipulability of the origin mechanism and the optimized mechanism are compared, the result shows that the optimized one is much better. The global dynamic condition number index has good effect in evaluating the dynamic dexterity of the whole workspace, and is efficient in the dynamic optimal design of the parallel manipulator.
基金supported by National Natural Science Foundation of China (Grant No. 50675095)
文摘Dynamic optimization of electromechanical coupling system is a significant engineering problem in the field of mechatronics. The performance improvement of electromechanical equipment depends on the system design parameters. Aiming at the spindle unit of refitted machine tool for solid rocket, the vibration acceleration of tool is taken as objective function, and the electromechanical system design parameters are appointed as design variables. Dynamic optimization model is set up by adopting Lagrange-Maxwell equations, Park transform and electromechanical system energy equations. In the procedure of seeking high efficient optimization method, exponential function is adopted to be the weight function of particle swarm optimization algorithm. Exponential inertia weight particle swarm algorithm(EPSA), is formed and applied to solve the dynamic optimization problem of electromechanical system. The probability density function of EPSA is presented and used to perform convergence analysis. After calculation, the optimized design parameters of the spindle unit are obtained in limited time period. The vibration acceleration of the tool has been decreased greatly by the optimized design parameters. The research job in the paper reveals that the problem of dynamic optimization of electromechanical system can be solved by the method of combining system dynamic analysis with reformed swarm particle optimizati on. Such kind of method can be applied in the design of robots, NC machine, and other electromechanical equipments.
基金supported by the National Natural Science Foundation of China (6087309960775013)
文摘In dynamic environments,it is important to track changing optimal solutions over time.Univariate marginal distribution algorithm(UMDA) which is a class algorithm of estimation of distribution algorithms attracts more and more attention in recent years.In this paper a new multi-population and diffusion UMDA(MDUMDA) is proposed for dynamic multimodal problems.The multi-population approach is used to locate multiple local optima which are useful to find the global optimal solution quickly to dynamic multimodal problems.The diffusion model is used to increase the diversity in a guided fashion,which makes the neighbor individuals of previous optimal solutions move gradually from the previous optimal solutions and enlarge the search space.This approach uses both the information of current population and the part history information of the optimal solutions.Finally experimental studies on the moving peaks benchmark are carried out to evaluate the proposed algorithm and compare the performance of MDUMDA and multi-population quantum swarm optimization(MQSO) from the literature.The experimental results show that the MDUMDA is effective for the function with moving optimum and can adapt to the dynamic environments rapidly.
基金supported by China Armament Pre-research Foundation(Grant No. 51318010402)UK Engineering and Physical Science Research Council (EPSRC), and China Scholarship Council (Grant No.2010611054)
文摘Work on dynamic topology optimization of engineering structures for vibration suppression has mainly addressed the maximization of eigenfrequencies and gaps between consecutive eigenfrequencies of free vibration, minimization of the dynamic compliance subject to forced vibration, and minimization of the structural frequency response. A dynamic topology optimization method of bi-material plate structures is presented based on power flow analysis. Topology optimization problems formulated directly with the design objective of minimizing the power flow response are dealt with. In comparison to the displacement or velocity response, the power flow response takes not only the amplitude of force and velocity into account, but also the phase relationship of the two vector quantities. The complex expression of power flow response is derived based on time-harmonic external mechanical loading and Rayleigh damping. The mathematical formulation of topology optimization is established based on power flow response and bi-material solid isotropic material with penalization(SIMP) model. Computational optimization procedure is developed by using adjoint design sensitivity analysis and the method of moving asymptotes(MMA). Several numerical examples are presented for bi-material plate structures with different loading frequencies, which verify the feasibility and effectiveness of this method. Additionally, optimum results between topological design of minimum power flow response and minimum dynamic compliance are compared, showing that the present method has strong adaptability for structural dynamic topology optimization problems. The proposed research provides a more accurate and effective approach for dynamic topology optimization of vibrating structures.
基金supported by the National Natural Science Foundation of China (60374063)the Natural Science Basic Research Plan Project in Shaanxi Province (2006A12)+1 种基金the Science and Technology Research Project of the Educational Department in Shaanxi Province (07JK180)the Emphasis Research Plan Project of Baoji University of Arts and Science (ZK0840)
文摘A new method to solve dynamic nonlinear constrained optimization problems (DNCOP) is proposed. First, the time (environment) variable period of DNCOP is divided into several equal subperiods. In each subperiod, the DNCOP is approximated by a static nonlinear constrained optimization problem (SNCOP). Second, for each SNCOP, inspired by the idea of multiobjective optimization, it is transformed into a static bi-objective optimization problem. As a result, the original DNCOP is approximately transformed into several static bi-objective optimization problems. Third, a new multiobjective evolutionary algorithm is proposed based on a new selection operator and an improved nonuniformity mutation operator. The simulation results indicate that the proposed algorithm is effective for DNCOP.
基金supported in part by National Key Research and Development Program of China(2016YFB0901900)the Science and Technology Foundation of GEIDCO(SGGEIG00JYJS1900016)
文摘Decarbonization of the electricity sector is crucial to mitigate the impacts of climate change and global warming over the coming decades.The key challenges for achieving this goal are carbon emission trading and electricity sector regulation,which are also the major components of the carbon and electricity markets,respectively.In this paper,a joint electricity and carbon market model is proposed to investigate the relationships between electricity price,carbon price,and electricity generation capacity,thereby identifying pathways toward a renewable energy transition under the transactional energy interconnection framework.The proposed model is a dynamically iterative optimization model consisting of upper-level and lower-level models.The upper-level model optimizes power generation and obtains the electricity price,which drives the lower-level model to update the carbon price and electricity generation capacity.The proposed model is verified using the Northeast Asia power grid.The results show that increasing carbon price will result in increased electricity price,along with further increases in renewable energy generation capacity in the following period.This increase in renewable energy generation will reduce reliance on carbon-emitting energy sources,and hence the carbon price will decline.Moreover,the interconnection among zones in the Northeast Asia power grid will enable reasonable allocation of zonal power generation.Carbon capture and storage (CCS) will be an effective technology to reduce the carbon emissions and further realize the emission reduction targets in 2030-2050.It eases the stress of realizing the energy transition because of the less urgency to install additional renewable energy capacity.
基金Key Science-Technology Foundation of Hunan Province, China (No. 05GK2007).
文摘Associated dynamic performance of the clamping force control valve used in continuously variable transmission (CVT) is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dynamic model is set up by means of mechanism analysis. For the purpose of checking the validity of the modeling method, a prototype workpiece of the valve is manufactured for comparison test, and its simulation result follows the experimental result quite well. An associated performance index is founded considering the response time, overshoot and saving energy, and five structural parameters are selected to adjust for deriving the optimal associated performance index. The optimization problem is solved by the genetic algorithm (GA) with necessary constraints. Finally, the properties of the optimized valve are compared with those of the prototype workpiece, and the results prove that the dynamic performance indexes of the optimized valve are much better than those of the prototype workpiece.
基金This work was supportedbytheNationalNaturalScienceFoundationofChina(No.60474051),theProgramforNewCenturyExcellentTalentsinUniversityofChina(NCET),andtheSpecializedResearchFundfortheDoctoralProgramofHigherEducationofChina(No.20020248028).
文摘A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation (DISOPE) was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.
文摘This paper first introduces the technical requirements for autonomous flight, with a brief review of the International Academy of Astronautics(IAA) study group, "autonomous dynamic trajectory optimization control of launch vehicle". Two research scenarios, ascent rescue and powered descent, are compared from the viewpoint of optimal control. On this basis, the technologies on the autonomous trajectory planning and control under the thrust-drop failures in the ascending phase, and the autonomous guidance method during the powered landing for the recovery of the rockets are discussed respectively. For the ascending problem, the characteristics of different solutions, including the iterative guidance method(IGM)-based residual carrying capacity evaluation, the state-triggered indices(STI), the joint planning with the payload’s performance, and the multiple graded optimization(MGO), are analyzed for comparison. For the landing problem, the challenges such as the feasible region reduction caused by high thrust weight ratio(HTWR) and the disturbance adaptability brought by the limited feasible region, are studied in detail, as well as the onboard planning demonstration flight in China are introduced. Finally, the foundations supporting the above methods are summarized, which play an important role in promoting the flight autonomy.
基金supported by the National Natural Science Foundation of China (11072014 and 11172018)
文摘In this paper, a minimax design of damped dynamic vibration absorber for a damped primary system is investigated to minimize the vibration magnitude peaks. Moreover, to reduce the sensitivity of the primary system response to variations of the forcing frequency for a two- degree-of-freedom system, the primary system should have two equal resonance magnitude peaks. To meet this re- quirement, a set of simplified constraint equations includ- ing distribution characteristics of the resonant frequencies of the primary system is established for the minimax objective function. The modified constraint equations have less un- known variables than those by other authors, which not only simplifies the computation but also improves the accuracy of the optimal values. The advantage of the proposed method is illustrated through numerical simulations.
文摘Time and space complexity is themost critical problemof the current routing optimization algorithms for Software Defined Networking(SDN).To overcome this complexity,researchers use meta-heuristic techniques inside the routing optimization algorithms in the OpenFlow(OF)based large scale SDNs.This paper proposes a hybrid meta-heuristic algorithm to optimize the dynamic routing problem for the large scale SDNs.Due to the dynamic nature of SDNs,the proposed algorithm uses amutation operator to overcome the memory-based problem of the ant colony algorithm.Besides,it uses the box-covering method and the k-means clustering method to divide the SDN network to overcome the problemof time and space complexity.The results of the proposed algorithm compared with the results of other similar algorithms and it shows that the proposed algorithm can handle the dynamic network changing,reduce the network congestion,the delay and running times and the packet loss rates.
文摘Using the dynamic optimization theory, we described a decision-making model for farmer choosing land use when there are several different kinds of uses for land. To obtain an empirical model that could be easily applied, decision rules for farmer with a single static expectation were given.
基金supported by the National Social Science Foundation of China in 2012 under Grant No. 11GJ003-074the Science Foundation of Aeronautics of China under Grant No. 20085584010
文摘Cooperative path dynamic planning of a UCAV (unmanned combat air vehicle) team not only considers the capability of task requirement of single UCAV, but also considers the cooperative dynamic connection among members of the UCAV team. A cooperative path dynamic planning model of the UCAV team by applying a global optimization method is discussed in this paper and the corresponding model is built and analyzed. By the example simulation, the reasonable result acquired indicates that the model could meet dynamic planning demand under the circumstance of membership functions. The model is easy to be realized and has good practicability.