In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed metho...In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.展开更多
At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive...At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive evaluation the advanced operation research techniques can be used in continuous production systems in developing countries very widely, because of initial inadequate plant layout, stage by stage development of production lines, the purchase of second hand machineries from various countries, plurality of customers. A case of production system planning is proposed for a chemical company in which the above mentioned conditions are almost presented. The goals and constraints in this issue are as follows: (1) Minimizing deviation of customer's requirements. (2) Maximizing the profit. (3) Minimizing the frequencies of changes in formula production. (4) Minimizing the inventory of final products. (5) Balancing the production sections with regard to rate in production. (6) Limitation in inventory of raw material. The present situation is in such a way that various techniques such as goal programming, linear programming and dynamic programming can be used. But dynamic production programming issues are divided into two categories, at first one with limitation in production capacity and another with unlimited production capacity. For the first category, a systematic and acceptable solution has not been presented yet. Therefore an innovative method is used to convert the dynamic situation to a zero- one model. At last this issue is changed to a goal programming model with non-linear limitations with the use of GRG algorithm and that's how it is solved.展开更多
The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark a...The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark analysis employs dynamic programming by backward induction to determine the globally optimal solution by solving the energy management problem starting at the final timestep and proceeding backwards in time. This method requires the development of a backwards facing model that propagates the wheel speed of the vehicle for the given drive cycle through the driveline components to determine the operating points of the powertrain. Although dynamic programming only searches the solution space within the feasible regions of operation, the benchmarking model must be solved for every admissible state at every timestep leading to strict requirements for runtime and memory. The backward facing model employs the quasi-static assumption of powertrain operation to reduce the fidelity of the model to accommodate these requirements. Verification and validation testing of the dynamic programming algorithm is conducted to ensure successful operation of the algorithm and to assess the validity of the determined control policy against a high-fidelity forward-facing vehicle model with a percent difference of fuel consumption of 1.2%. The benchmark analysis is conducted over multiple drive cycles to determine the optimal control policy that provides a benchmark for real-time algorithm development and determines control trends that can be used to improve existing algorithms. The optimal combined charge sustaining fuel economy of the vehicle is determined by the dynamic programming algorithm to be 32.99 MPG, a 52.6% increase over the stock 3.6 L 2019 Chevrolet Blazer.展开更多
A good hybrid vehicle control strategy cannot only meet the power requirements of the vehicle,but also effectively save fuel and reduce emissions.In this paper,the construction of model predictive control in hybrid el...A good hybrid vehicle control strategy cannot only meet the power requirements of the vehicle,but also effectively save fuel and reduce emissions.In this paper,the construction of model predictive control in hybrid electric vehicle is proposed.The solving process and the use of reference trajectory are discussed for the application of MPC based on dynamic programming algorithm.The simulation of hybrid electric vehicle is carried out under a specific working condition.The simulation results show that the control strategy can effectively reduce fuel consumption when the torque of engine and motor is reasonably distributed,and the effectiveness of the control strategy is verified.展开更多
When acquaintances of a model are little or the model is too complicate to build by using traditional time series methods, it is convenient for us to take advantage of genetic programming (GP) to build the model. Cons...When acquaintances of a model are little or the model is too complicate to build by using traditional time series methods, it is convenient for us to take advantage of genetic programming (GP) to build the model. Considering the complexity of nonlinear dynamic systems, this paper proposes modeling dynamic systems by using the nonlinear difference e-quation based on GP technique. First it gives the method, criteria and evaluation of modeling. Then it describes the modeling algorithm using GP. Finally two typical examples of time series are used to perform the numerical experiments. The result shows that this algorithm can successfully establish the difference equation model of dynamic systems and its predictive result is also satisfactory.展开更多
In a multi-agent system, each agent must adapt itself to the environment and coordinate with other agents dynamically. TO predict or cooperate with the behavior of oiller agents. An agent should dynamically establish ...In a multi-agent system, each agent must adapt itself to the environment and coordinate with other agents dynamically. TO predict or cooperate with the behavior of oiller agents. An agent should dynamically establish and evolve the cooperative behavior model of itself. In this paper, we represent the behavior model of an agent as a f-mite state machine and propose a new method of dynamically evolving the behavior model of an agent by evolutionary programming.展开更多
A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block mode...A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block modeling method uses the modules of a six tuple to form a rule based solution model. Moreover, a rule based system has been designed and set up to solve the Dynamic Programming Model. This knowledge based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynamic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Programming Model can also be conveniently realized in computer.展开更多
A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical an...A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.展开更多
A dynamic food chain model and program, DYFOM 95, for predicting the radiological consequences of nuclear accident has been developed, which is not only suitable to the West food chain but also to Chinese food chain. ...A dynamic food chain model and program, DYFOM 95, for predicting the radiological consequences of nuclear accident has been developed, which is not only suitable to the West food chain but also to Chinese food chain. The following processes, caused by accident release which will make an impact on radionuclide concentration in the edible parts of vegetable were considered: dry and wet deposition interception and initial retention, translocation, percolation, root uptake and tillage. Activity intake rate of animals, effects of processing and activity intake of human through ingestion pathway ware also considered in calculations. The effects of leaf area index LAI of vegetable were considered in dry deposition model. A method for calculating the contribution of rain with different period and different intensity to total wet deposition was established. The program contains 1 main code and 5 sub codes to calculate dry and wet deposition on surface of vegetable and soil, translocation of nuclides in vegetable, nuclide concentration in the edible parts of vegetable and in animal products and activity intake of human and so on.展开更多
This paper is concerned with the relationship between maximum principle and dynamic programming in zero-sum stochastic differential games. Under the assumption that the value function is enough smooth, relations among...This paper is concerned with the relationship between maximum principle and dynamic programming in zero-sum stochastic differential games. Under the assumption that the value function is enough smooth, relations among the adjoint processes, the generalized Hamiltonian function and the value function are given. A portfolio optimization problem under model uncertainty in the financial market is discussed to show the applications of our result.展开更多
To improve the operation situation of difficulty and low efficiency in the extraction of fermented grains(FG),a high-load and large-workspace reclaiming robot for ceramic cylinder fermentation is designed,and a reclai...To improve the operation situation of difficulty and low efficiency in the extraction of fermented grains(FG),a high-load and large-workspace reclaiming robot for ceramic cylinder fermentation is designed,and a reclaiming effector is designed according to the operating characteristics.Firstly,the kinematics and singularity of the mechanism are analyzed.A multi-domain polar coordinate search method is proposed to obtain the workspace and the volume of the mechanism.Secondly,the dynamic modeling is completed and the example simulation is carried out.Thirdly,the motion-force transmission index of the mechanism is established.And based on the global transmissibility and the good-transmission workspace,the dimensional synthesis of the driving mechanism is completed by using the performance atlas-based method.Finally,aiming at the regular workspace size,stiffness and loading capacity,the Pareto optimal solution set of the executive mechanism dimension is obtained by using the multi-objective particle swarm optimization(MOPSO)algorithm.This paper can provide a theoretical basis for the optimal design and control of FG reclaiming robot.展开更多
Modulating both the clock frequency and supply voltage of the network-on-chip (NoC) during runtime can reduce the power consumption and heat flux, but will lead to the increase of the latency of NoC. It is necessary...Modulating both the clock frequency and supply voltage of the network-on-chip (NoC) during runtime can reduce the power consumption and heat flux, but will lead to the increase of the latency of NoC. It is necessary to find a tradeoff between power consumption and communication latency. So we propose an analytical latency model which can show us the relationship of them. The proposed model to analyze latency is based on the M/G/1 queuing model, which is suitable for dynamic frequency scaling. The experiment results show that the accuracy of this model is more than 90%.展开更多
A properly designed public transport system is expected to improve traffic efficiency.A high-frequency bus service would decrease the waiting time for passengers,but the interaction between buses and cars might result...A properly designed public transport system is expected to improve traffic efficiency.A high-frequency bus service would decrease the waiting time for passengers,but the interaction between buses and cars might result in more serious congestion.On the other hand,a low-frequency bus service would increase the waiting time for passengers and would not reduce the use of private cars.It is important to strike a balance between high and low frequencies in order to minimize the total delays for all road users.It is critical to formulate the impacts of bus frequency on congestion dynamics and mode choices.However,as far as the authors know,most proposed bus frequency optimization formulations are based on static demand and the Bureau of Public Roads function,and do not properly consider the congestion dynamics and their impacts on mode choices.To fill this gap,this paper proposes a bi-level optimization model.A three-dimensional Macroscopic Fundamental Diagram based modeling approach is developed to capture the bi-modal congestion dynamics.A variational inequality model for the user equilibrium in mode choices is presented and solved using a double projection algorithm.A surrogate model-based algorithm is used to solve the bi-level programming problem.展开更多
The mathematical and statistical modeling of the problem of poverty is a major challenge given Burundi’s economic development. Innovative economic optimization systems are widely needed to face the problem of the dyn...The mathematical and statistical modeling of the problem of poverty is a major challenge given Burundi’s economic development. Innovative economic optimization systems are widely needed to face the problem of the dynamic of the poverty in Burundi. The Burundian economy shows an inflation rate of -1.5% in 2018 for the Gross Domestic Product growth real rate of 2.8% in 2016. In this research, the aim is to find a model that contributes to solving the problem of poverty in Burundi. The results of this research fill the knowledge gap in the modeling and optimization of the Burundian economic system. The aim of this model is to solve an optimization problem combining the variables of production, consumption, budget, human resources and available raw materials. Scientific modeling and optimal solving of the poverty problem show the tools for measuring poverty rate and determining various countries’ poverty levels when considering advanced knowledge. In addition, investigating the aspects of poverty will properly orient development aid to developing countries and thus, achieve their objectives of growth and the fight against poverty. This paper provides a new and innovative framework for global scientific research regarding the multiple facets of this problem. An estimate of the poverty rate allows good progress with the theory and optimization methods in measuring the poverty rate and achieving sustainable development goals. By comparing the annual food production and the required annual consumption, there is an imbalance between different types of food. Proteins, minerals and vitamins produced in Burundi are sufficient when considering their consumption as required by the entire Burundian population. This positive contribution for the latter comes from the fact that some cows, goats, fishes, ···, slaughtered in Burundi come from neighboring countries. Real production remains in deficit. The lipids, acids, calcium, fibers and carbohydrates produced in Burundi are insufficient for consumption. This negative contribution proves a Burundian food deficit. It is a decision-making indicator for the design and updating of agricultural policy and implementation programs as well as projects. Investment and economic growth are only possible when food security is mastered. The capital allocated to food investment must be revised upwards. Demographic control is also a relevant indicator to push forward Burundi among the emerging countries in 2040. Meanwhile, better understanding of the determinants of poverty by taking cultural and organizational aspects into account guides managers for poverty reduction projects and programs.展开更多
<div style="text-align:justify;"> In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics ...<div style="text-align:justify;"> In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics model of the freight train operation process is established based on the safety and the freight train dynamics model in the process of its operation. The algorithm of combining elite competition strategy with multi-objective particle swarm optimization technology is introduced, and the winning particles are obtained through the competition between two elite particles to guide the update of other particles, so as to balance the convergence and distribution of multi-objective particle swarm optimization. The performance comparison experimental results verify the superiority of the proposed algorithm. The simulation experiments of the actual line verify the feasibility of the model and the effectiveness of the proposed algorithm. </div>展开更多
A new method of dynamic optimization for the flying trajectory of a free flying space robot based on its flying motion characteristics is presented. The continuous flying trajectory is broken into a number of segment ...A new method of dynamic optimization for the flying trajectory of a free flying space robot based on its flying motion characteristics is presented. The continuous flying trajectory is broken into a number of segment and the control efforts and the duration of the segment are chosen as the optimization parameters. The objective function is made by using the weighted sum of the fuel used and the time spent, and the constraint equations are selected. Finally, the internal point punishment function method is adopted in the optimization program, and the results of computer simulation are given.展开更多
Driven by the goal of“carbon neutrality,”the increase in use of renewable energy power systems will be inevitable in the future.Uncontrolled output power and random volatility make it difficult to balance power in r...Driven by the goal of“carbon neutrality,”the increase in use of renewable energy power systems will be inevitable in the future.Uncontrolled output power and random volatility make it difficult to balance power in real time during system operation.Therefore,energy storage is considered to be an effective way to ensure the real-time balance of system power.However,cost of energy storage is relatively expensive.As a solution,energy storage can be used to balance the system power in order to reduce system operating costs.Taking the high proportion of wind power systems as an example,the impact of the“supply side”low-carbon transformation on the economics and reliability of power system operation is explored.In order to solve the problem of power system operation configuration optimization under the background of“carbon neutrality,”this paper establishes a multi-objective programming model.展开更多
基金supported by the National Science Fund for Distinguished Young Scholars (62225303)the Fundamental Research Funds for the Central Universities (buctrc202201)+1 种基金China Scholarship Council,and High Performance Computing PlatformCollege of Information Science and Technology,Beijing University of Chemical Technology。
文摘In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.
基金supported by the Public Welfare Industry Special Fund Project of the Ministry of Water Resources of China (Grant No. 200701028)the Humanities and Social Science Foundation Program of Hohai University (Grant No. 2008421411)
文摘At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive evaluation the advanced operation research techniques can be used in continuous production systems in developing countries very widely, because of initial inadequate plant layout, stage by stage development of production lines, the purchase of second hand machineries from various countries, plurality of customers. A case of production system planning is proposed for a chemical company in which the above mentioned conditions are almost presented. The goals and constraints in this issue are as follows: (1) Minimizing deviation of customer's requirements. (2) Maximizing the profit. (3) Minimizing the frequencies of changes in formula production. (4) Minimizing the inventory of final products. (5) Balancing the production sections with regard to rate in production. (6) Limitation in inventory of raw material. The present situation is in such a way that various techniques such as goal programming, linear programming and dynamic programming can be used. But dynamic production programming issues are divided into two categories, at first one with limitation in production capacity and another with unlimited production capacity. For the first category, a systematic and acceptable solution has not been presented yet. Therefore an innovative method is used to convert the dynamic situation to a zero- one model. At last this issue is changed to a goal programming model with non-linear limitations with the use of GRG algorithm and that's how it is solved.
文摘The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark analysis employs dynamic programming by backward induction to determine the globally optimal solution by solving the energy management problem starting at the final timestep and proceeding backwards in time. This method requires the development of a backwards facing model that propagates the wheel speed of the vehicle for the given drive cycle through the driveline components to determine the operating points of the powertrain. Although dynamic programming only searches the solution space within the feasible regions of operation, the benchmarking model must be solved for every admissible state at every timestep leading to strict requirements for runtime and memory. The backward facing model employs the quasi-static assumption of powertrain operation to reduce the fidelity of the model to accommodate these requirements. Verification and validation testing of the dynamic programming algorithm is conducted to ensure successful operation of the algorithm and to assess the validity of the determined control policy against a high-fidelity forward-facing vehicle model with a percent difference of fuel consumption of 1.2%. The benchmark analysis is conducted over multiple drive cycles to determine the optimal control policy that provides a benchmark for real-time algorithm development and determines control trends that can be used to improve existing algorithms. The optimal combined charge sustaining fuel economy of the vehicle is determined by the dynamic programming algorithm to be 32.99 MPG, a 52.6% increase over the stock 3.6 L 2019 Chevrolet Blazer.
基金This work was supported by the youth backbone teachers training program of Henan colleges and universities under Grant No.2016ggjs-287the project of science and technology of Henan province under Grant Nos.172102210124,202102210269the Key Scientific Research projects in Colleges and Universities in Henan(Grant No.18B460003).
文摘A good hybrid vehicle control strategy cannot only meet the power requirements of the vehicle,but also effectively save fuel and reduce emissions.In this paper,the construction of model predictive control in hybrid electric vehicle is proposed.The solving process and the use of reference trajectory are discussed for the application of MPC based on dynamic programming algorithm.The simulation of hybrid electric vehicle is carried out under a specific working condition.The simulation results show that the control strategy can effectively reduce fuel consumption when the torque of engine and motor is reasonably distributed,and the effectiveness of the control strategy is verified.
基金Supported by Foundation for University Key Teacher by the Ministry of Education of China
文摘When acquaintances of a model are little or the model is too complicate to build by using traditional time series methods, it is convenient for us to take advantage of genetic programming (GP) to build the model. Considering the complexity of nonlinear dynamic systems, this paper proposes modeling dynamic systems by using the nonlinear difference e-quation based on GP technique. First it gives the method, criteria and evaluation of modeling. Then it describes the modeling algorithm using GP. Finally two typical examples of time series are used to perform the numerical experiments. The result shows that this algorithm can successfully establish the difference equation model of dynamic systems and its predictive result is also satisfactory.
文摘In a multi-agent system, each agent must adapt itself to the environment and coordinate with other agents dynamically. TO predict or cooperate with the behavior of oiller agents. An agent should dynamically establish and evolve the cooperative behavior model of itself. In this paper, we represent the behavior model of an agent as a f-mite state machine and propose a new method of dynamically evolving the behavior model of an agent by evolutionary programming.
文摘A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block modeling method uses the modules of a six tuple to form a rule based solution model. Moreover, a rule based system has been designed and set up to solve the Dynamic Programming Model. This knowledge based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynamic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Programming Model can also be conveniently realized in computer.
文摘A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.
文摘A dynamic food chain model and program, DYFOM 95, for predicting the radiological consequences of nuclear accident has been developed, which is not only suitable to the West food chain but also to Chinese food chain. The following processes, caused by accident release which will make an impact on radionuclide concentration in the edible parts of vegetable were considered: dry and wet deposition interception and initial retention, translocation, percolation, root uptake and tillage. Activity intake rate of animals, effects of processing and activity intake of human through ingestion pathway ware also considered in calculations. The effects of leaf area index LAI of vegetable were considered in dry deposition model. A method for calculating the contribution of rain with different period and different intensity to total wet deposition was established. The program contains 1 main code and 5 sub codes to calculate dry and wet deposition on surface of vegetable and soil, translocation of nuclides in vegetable, nuclide concentration in the edible parts of vegetable and in animal products and activity intake of human and so on.
文摘This paper is concerned with the relationship between maximum principle and dynamic programming in zero-sum stochastic differential games. Under the assumption that the value function is enough smooth, relations among the adjoint processes, the generalized Hamiltonian function and the value function are given. A portfolio optimization problem under model uncertainty in the financial market is discussed to show the applications of our result.
基金supported by the National Natural Science Foundation of China(No.51905367)。
文摘To improve the operation situation of difficulty and low efficiency in the extraction of fermented grains(FG),a high-load and large-workspace reclaiming robot for ceramic cylinder fermentation is designed,and a reclaiming effector is designed according to the operating characteristics.Firstly,the kinematics and singularity of the mechanism are analyzed.A multi-domain polar coordinate search method is proposed to obtain the workspace and the volume of the mechanism.Secondly,the dynamic modeling is completed and the example simulation is carried out.Thirdly,the motion-force transmission index of the mechanism is established.And based on the global transmissibility and the good-transmission workspace,the dimensional synthesis of the driving mechanism is completed by using the performance atlas-based method.Finally,aiming at the regular workspace size,stiffness and loading capacity,the Pareto optimal solution set of the executive mechanism dimension is obtained by using the multi-objective particle swarm optimization(MOPSO)algorithm.This paper can provide a theoretical basis for the optimal design and control of FG reclaiming robot.
基金supported by the National Natural Science Foundation of China under Grant No.61376024 and No.61306024Natural Science Foundation of Guangdong Province under Grant No.S2013040014366Basic Research Programme of Shenzhen No.JCYJ20140417113430642 and JCYJ20140901003939020
文摘Modulating both the clock frequency and supply voltage of the network-on-chip (NoC) during runtime can reduce the power consumption and heat flux, but will lead to the increase of the latency of NoC. It is necessary to find a tradeoff between power consumption and communication latency. So we propose an analytical latency model which can show us the relationship of them. The proposed model to analyze latency is based on the M/G/1 queuing model, which is suitable for dynamic frequency scaling. The experiment results show that the accuracy of this model is more than 90%.
基金supported by the National Natural Science Foundation of China(Grant No.72201088,71871077,71925001)the Fundamental Research Funds for the Central Universities of China(Grant No.PA2022GDSK0040,JZ2023YQTD0073),which are gratefully acknowledged.
文摘A properly designed public transport system is expected to improve traffic efficiency.A high-frequency bus service would decrease the waiting time for passengers,but the interaction between buses and cars might result in more serious congestion.On the other hand,a low-frequency bus service would increase the waiting time for passengers and would not reduce the use of private cars.It is important to strike a balance between high and low frequencies in order to minimize the total delays for all road users.It is critical to formulate the impacts of bus frequency on congestion dynamics and mode choices.However,as far as the authors know,most proposed bus frequency optimization formulations are based on static demand and the Bureau of Public Roads function,and do not properly consider the congestion dynamics and their impacts on mode choices.To fill this gap,this paper proposes a bi-level optimization model.A three-dimensional Macroscopic Fundamental Diagram based modeling approach is developed to capture the bi-modal congestion dynamics.A variational inequality model for the user equilibrium in mode choices is presented and solved using a double projection algorithm.A surrogate model-based algorithm is used to solve the bi-level programming problem.
文摘The mathematical and statistical modeling of the problem of poverty is a major challenge given Burundi’s economic development. Innovative economic optimization systems are widely needed to face the problem of the dynamic of the poverty in Burundi. The Burundian economy shows an inflation rate of -1.5% in 2018 for the Gross Domestic Product growth real rate of 2.8% in 2016. In this research, the aim is to find a model that contributes to solving the problem of poverty in Burundi. The results of this research fill the knowledge gap in the modeling and optimization of the Burundian economic system. The aim of this model is to solve an optimization problem combining the variables of production, consumption, budget, human resources and available raw materials. Scientific modeling and optimal solving of the poverty problem show the tools for measuring poverty rate and determining various countries’ poverty levels when considering advanced knowledge. In addition, investigating the aspects of poverty will properly orient development aid to developing countries and thus, achieve their objectives of growth and the fight against poverty. This paper provides a new and innovative framework for global scientific research regarding the multiple facets of this problem. An estimate of the poverty rate allows good progress with the theory and optimization methods in measuring the poverty rate and achieving sustainable development goals. By comparing the annual food production and the required annual consumption, there is an imbalance between different types of food. Proteins, minerals and vitamins produced in Burundi are sufficient when considering their consumption as required by the entire Burundian population. This positive contribution for the latter comes from the fact that some cows, goats, fishes, ···, slaughtered in Burundi come from neighboring countries. Real production remains in deficit. The lipids, acids, calcium, fibers and carbohydrates produced in Burundi are insufficient for consumption. This negative contribution proves a Burundian food deficit. It is a decision-making indicator for the design and updating of agricultural policy and implementation programs as well as projects. Investment and economic growth are only possible when food security is mastered. The capital allocated to food investment must be revised upwards. Demographic control is also a relevant indicator to push forward Burundi among the emerging countries in 2040. Meanwhile, better understanding of the determinants of poverty by taking cultural and organizational aspects into account guides managers for poverty reduction projects and programs.
文摘<div style="text-align:justify;"> In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics model of the freight train operation process is established based on the safety and the freight train dynamics model in the process of its operation. The algorithm of combining elite competition strategy with multi-objective particle swarm optimization technology is introduced, and the winning particles are obtained through the competition between two elite particles to guide the update of other particles, so as to balance the convergence and distribution of multi-objective particle swarm optimization. The performance comparison experimental results verify the superiority of the proposed algorithm. The simulation experiments of the actual line verify the feasibility of the model and the effectiveness of the proposed algorithm. </div>
文摘A new method of dynamic optimization for the flying trajectory of a free flying space robot based on its flying motion characteristics is presented. The continuous flying trajectory is broken into a number of segment and the control efforts and the duration of the segment are chosen as the optimization parameters. The objective function is made by using the weighted sum of the fuel used and the time spent, and the constraint equations are selected. Finally, the internal point punishment function method is adopted in the optimization program, and the results of computer simulation are given.
文摘Driven by the goal of“carbon neutrality,”the increase in use of renewable energy power systems will be inevitable in the future.Uncontrolled output power and random volatility make it difficult to balance power in real time during system operation.Therefore,energy storage is considered to be an effective way to ensure the real-time balance of system power.However,cost of energy storage is relatively expensive.As a solution,energy storage can be used to balance the system power in order to reduce system operating costs.Taking the high proportion of wind power systems as an example,the impact of the“supply side”low-carbon transformation on the economics and reliability of power system operation is explored.In order to solve the problem of power system operation configuration optimization under the background of“carbon neutrality,”this paper establishes a multi-objective programming model.