Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to en...Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to engineering requirements, aiming to optimize satellite heat dissipation while considering constraints on static stability, 3D geometric relationships between components, and special component positions. The 3D-SCALO problem is a challenging bilevel combinatorial optimization task, involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer,with both influencing each other. To address this issue, first, a Mixed Integer Programming(MIP) model is proposed, which reformulates the original bilevel problem into a single-level optimization problem, enabling the exploration of a more comprehensive optimization space while avoiding iterative nested optimization. Then, to model the 3D geometric relationships between components within the MIP framework, a linearized 3D Phi-function method is proposed, which handles non-overlapping and safety distance constraints between cuboid components in an explicit and effective way. Subsequently, the Finite-Rectangle Method(FRM) is proposed to manage 3D geometric constraints for complex-shaped components by approximating them with a finite set of cuboids, extending the applicability of the geometric modeling approach. Finally, the feasibility and effectiveness of the proposed MIP model are demonstrated through two numerical examples"and a real-world engineering case, which confirms its suitability for complex-shaped components and real engineering applications.展开更多
Considering the decision-making variables of the capacities of branch roads and the optimization targets of lowering the saturation of arterial roads and the reconstruction expense of branch roads, the bi-level progra...Considering the decision-making variables of the capacities of branch roads and the optimization targets of lowering the saturation of arterial roads and the reconstruction expense of branch roads, the bi-level programming model for reconstructing the branch roads was set up. The upper level model was for determining the enlarged capacities of the branch roads, and the lower level model was for calculating the flows of road sections via the user equilibrium traffic assignment method. The genetic algorithm for solving the bi-level model was designed to obtain the reconstruction capacities of the branch roads. The results show that by the bi-level model and its algorithm, the optimum scheme of urban branch roads reconstruction can be gained, which reduces the saturation of arterial roads apparently, and alleviates traffic congestion. In the data analysis the arterial saturation decreases from 1.100 to 0.996, which verifies the micro-circulation transportation's function of urban branch road network.展开更多
The automatic algorithm programming model can increase the dependability and efficiency of algorithm program development,including specification generation,program refinement,and formal verification.However,the existi...The automatic algorithm programming model can increase the dependability and efficiency of algorithm program development,including specification generation,program refinement,and formal verification.However,the existing model has two flaws:incompleteness of program refinement and inadequate automation of formal verification.This paper proposes an automatic algorithm programming model based on the improved Morgan’s refinement calculus.It extends the Morgan’s refinement calculus rules and designs the C++generation system for realizing the complete process of refinement.Meanwhile,the automation tools VCG(Verification Condition Generator)and Isabelle are used to improve the automation of formal verification.An example of a stock’s maximum income demonstrates the effectiveness of the proposed model.Furthermore,the proposed model has some relevance for automatic software generation.展开更多
The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and wate...The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and water sectors within a basin. With the precondition of strictly controlling maximum emissions rights, initial water rights were allocated between the first and the second levels of the hierarchy in order to promote fair and coordinated development across different regions of the basin and coordinated and efficient water use across different water sectors, realize the maximum comprehensive benefits to the basin, promote the unity of quantity and quality of initial water rights allocation, and eliminate water conflict across different regions and water sectors. According to interactive decision-making theory, a principal-subordinate hierarchical interactive iterative algorithm based on the satisfaction degree was developed and used to solve the initial water rights allocation model. A case study verified the validity of the model.展开更多
In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed sign...In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.展开更多
A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' pa...A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' parameters are available from the geological database of the mine. The objective is to minimize the deviation of the average ore grade of blasted blocks from the standard ore grade required by the mill. Transportation ability constraint. production quantity demand constraint. minimum safety bench constraint. block size constraint and block, bench precedence constraints are considered in forming the programming model. This model has more practical objective function and reasonable constraints compared with the existing model for this kind of problems.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
The refugee immigration problem can be considered as a special “transportation problem”. Linear Programming Model is built, where two objectives with weight in the objective function, for the shortest routes that th...The refugee immigration problem can be considered as a special “transportation problem”. Linear Programming Model is built, where two objectives with weight in the objective function, for the shortest routes that the refugees go along and the minimum number of refugees stayed in each country. An example of EU is introduced and calculated on Lingo software. The results show that the model is available to solve the refugee immigration problem in different scale.展开更多
As one part of the Landstad International Metropolitan Area,Utrecht has become known as one of the best tourist destinations in recent years,with the rapid growth of worldwide travel trends.In this paper,through the a...As one part of the Landstad International Metropolitan Area,Utrecht has become known as one of the best tourist destinations in recent years,with the rapid growth of worldwide travel trends.In this paper,through the adaption of the linear programming model,the paper intends to not only quantify the optimum number of visitors to Utrecht but also formulate a number of policy recommendations based on the reconstruction of this optimum.The paper draws the following conclusions:(1) tourist carrying capacity of Utrecht is not yet exceeded;(2) restrictive accommodation policy does not currently seem necessary;(3) the cultural-historical attractions are not yet optimally used;(4) investing in strategic provisions is currently not necessary.And from the conclusion,the paper further puts forward the following suggestions on the city’s tourism development strategy:(1) to identify "tourist flood plains";(2) to encourage the tourist disclosure of these alternatives;(3) to invest even more explicitly in residential tourism and,where possible,curb day tourism;(4) to introduce a new business model.展开更多
Ensuring the safe evacuation of miners during fire emergencies in the shortest possible time is one of the most critical aspects of underground mining operations.Despite advances in mining evacuation methods,little re...Ensuring the safe evacuation of miners during fire emergencies in the shortest possible time is one of the most critical aspects of underground mining operations.Despite advances in mining evacuation methods,little research has been conducted on mine vehicles in this context.This study proposed a vehicle-augmented evacuation integer programming(VEIP)model to minimize the total evacuation cost as a function of the required evacuation time during fire emergencies.This approach aims to minimize the risk of miners being exposed to dangerous fire conditions by strategically integrating mine vehicles into the evacuation procedure.The approach determines the optimal evacuation path for each miner,considering factors such as available mine vehicles,miners’locations,refuge chambers,and fresh-air bases.To validate the effectiveness of the developed VEIP model,a case study was conducted using the mine layout of the Turquoise Ridge Underground Mine in the United States.Furthermore,a statistical comparison was conducted between the VEIP model and the evacuation integer programming(EIP)model,tailored to evacuation on foot,to emphasize vehicles’influence on the evacuation process.The results showed that integrating mine vehicles into evacuation procedures significantly reduces the total evacuation time.A cost savings analysis in the VEIP model revealed that the evacuation time savings increase exponentially as the number of miners present during evacuation increases.The potential benefits of using mine vehicles to improve the efficiency of evacuation from underground mine fires were highlighted in this study.展开更多
To establish the optimal reference trajectory for a near-space vehicle under free terminal time,a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization.First,the mod...To establish the optimal reference trajectory for a near-space vehicle under free terminal time,a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization.First,the model predictive static programming method is developed by incorporating neighboring terms and trust region,enabling rapid generation of precise optimal solutions.Next,an adaptive fish swarm optimization technique is employed to identify a sub-optimal solution,while a momentum gradient descent method with learning rate decay ensures the convergence to the global optimal solution.To validate the feasibility and accuracy of the proposed method,a near-space vehicle example is analyzed and simulated during its glide phase.The simulation results demonstrate that the proposed method aligns with theoretical derivations and outperforms existing methods in terms of convergence speed and accuracy.Therefore,the proposed method offers significant practical value for solving the fast trajectory optimization problem in near-space vehicle applications.展开更多
This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from g...This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from graphic-centric processors to versatile computing units,it delves into the nuanced optimization of memory access,thread management,algorithmic design,and data structures.These optimizations are critical for exploiting the parallel processing capabilities of GPUs,addressingboth the theoretical frameworks and practical implementations.By integrating advanced strategies such as memory coalescing,dynamic scheduling,and parallel algorithmic transformations,this research aims to significantly elevate computational efficiency and throughput.The findings underscore the potential of optimized GPU programming to revolutionize computational tasks across various domains,highlighting a pathway towards achieving unparalleled processing power and efficiency in HPC environments.The paper not only contributes to the academic discourse on GPU optimization but also provides actionable insights for developers,fostering advancements in computational sciences and technology.展开更多
Unified programming models can effectively improve program portability on various heterogeneous high-performance computers.Existing unified programming models put a lot of effort to code portability but are still far ...Unified programming models can effectively improve program portability on various heterogeneous high-performance computers.Existing unified programming models put a lot of effort to code portability but are still far from achieving good performance portability.In this paper,we present a preliminary design of a performance-portable unified programming model including four aspects:programming language,programming abstraction,compilation optimization,and scheduling system.Specifically,domain-specific languages introduce domain knowledge to decouple the optimizations for different applications and architectures.The unified programming abstraction unifies the common features of different architectures to support common optimizations.Multi-level compilation optimization enables comprehensive performance optimization based on multi-level intermediate representations.Resource-aware lightweight runtime scheduling system improves the resource utilization of heterogeneous computers.This is a perspective paper to show our viewpoints on programming models for emerging heterogeneous systems.展开更多
This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) ...This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.展开更多
This study combines multi-regional inputoutput(MRIO)model with linear programming(LP)model to explore economic structure adjustment strategies for the reduction of carbon dioxide(CO_(2))emissions.A particular feature ...This study combines multi-regional inputoutput(MRIO)model with linear programming(LP)model to explore economic structure adjustment strategies for the reduction of carbon dioxide(CO_(2))emissions.A particular feature of this study is the identification of the optimal regulation sequence of final products in various regions to reduce CO_(2)emissions with the minimum loss in gross domestic product(GDP).By using China's MRIO tables 2017 with 28 regions and 42 economic sectors,results show that reduction in final demand leads to simultaneous reductions in GDP and CO_(2)emissions.Nevertheless,certain demand side regulation strategy can be adopted to lower CO_(2)emissions at the smallest loss of economic growth.Several key final products,such as metallurgy,nonmetal,metal,and chemical products,should first be regulated to reduce CO_(2)emissions at the minimum loss in GDP.Most of these key products concentrate in the coastal developed regions in China.The proposed MRIO-LP model considers the inter-relationship among various sectors and regions,and can aid policy makers in designing effective policy for industrial structure adjustment at the regional level to achieve the national environmental and economic targets.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
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
This paper presents a self-contained proof of Special Termination of MMP (Minimal Model Program). By refining the assumptions and simplifying the argument, it offers a more accessible approach compared to the original...This paper presents a self-contained proof of Special Termination of MMP (Minimal Model Program). By refining the assumptions and simplifying the argument, it offers a more accessible approach compared to the original proof in BCHM (Birkar-Cascini-Hacon-McKernan).展开更多
Plant invasion refers to the phenomenon that some plants grow too fast due to they are far away from the original living environment or predators, affecting the local environment. With the development of tourism and t...Plant invasion refers to the phenomenon that some plants grow too fast due to they are far away from the original living environment or predators, affecting the local environment. With the development of tourism and trade, the harm caused by invasive plants will be more and more serious. Therefore, it is necessary to ex- plore an effective method for controlling plant invasion through qualitative and quan- titative research. In this paper, the models were established for the early and late harmful plant invasion control. The huge computation was completed by the com- puter programming to obtain the optimal solutions of the models. The real meaning of the optimal solution was further discussed. Through numerical simulations and discussion, it could be concluded that the quantitative research on the invasive plant control had a certain application value.展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
基金supported by the National Natural Science Foundation of China(No.92371206)the Postgraduate Scientific Research Innovation Project of Hunan Province,China(No.CX2023063).
文摘Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to engineering requirements, aiming to optimize satellite heat dissipation while considering constraints on static stability, 3D geometric relationships between components, and special component positions. The 3D-SCALO problem is a challenging bilevel combinatorial optimization task, involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer,with both influencing each other. To address this issue, first, a Mixed Integer Programming(MIP) model is proposed, which reformulates the original bilevel problem into a single-level optimization problem, enabling the exploration of a more comprehensive optimization space while avoiding iterative nested optimization. Then, to model the 3D geometric relationships between components within the MIP framework, a linearized 3D Phi-function method is proposed, which handles non-overlapping and safety distance constraints between cuboid components in an explicit and effective way. Subsequently, the Finite-Rectangle Method(FRM) is proposed to manage 3D geometric constraints for complex-shaped components by approximating them with a finite set of cuboids, extending the applicability of the geometric modeling approach. Finally, the feasibility and effectiveness of the proposed MIP model are demonstrated through two numerical examples"and a real-world engineering case, which confirms its suitability for complex-shaped components and real engineering applications.
基金Project(2006CB705507) supported by the National Basic Research and Development Program of ChinaProject(20060533036) supported by the Specialized Research Foundation for the Doctoral Program of Higher Education of China
文摘Considering the decision-making variables of the capacities of branch roads and the optimization targets of lowering the saturation of arterial roads and the reconstruction expense of branch roads, the bi-level programming model for reconstructing the branch roads was set up. The upper level model was for determining the enlarged capacities of the branch roads, and the lower level model was for calculating the flows of road sections via the user equilibrium traffic assignment method. The genetic algorithm for solving the bi-level model was designed to obtain the reconstruction capacities of the branch roads. The results show that by the bi-level model and its algorithm, the optimum scheme of urban branch roads reconstruction can be gained, which reduces the saturation of arterial roads apparently, and alleviates traffic congestion. In the data analysis the arterial saturation decreases from 1.100 to 0.996, which verifies the micro-circulation transportation's function of urban branch road network.
基金Supported by the National Natural Science Foundation of China(61862033,61902162)Key Project of Science and Technology Research of Department of Education of Jiangxi Province(GJJ210307)Postgraduate Innovation Fund Project of Education Department of Jiangxi Province(YC2021-S306)。
文摘The automatic algorithm programming model can increase the dependability and efficiency of algorithm program development,including specification generation,program refinement,and formal verification.However,the existing model has two flaws:incompleteness of program refinement and inadequate automation of formal verification.This paper proposes an automatic algorithm programming model based on the improved Morgan’s refinement calculus.It extends the Morgan’s refinement calculus rules and designs the C++generation system for realizing the complete process of refinement.Meanwhile,the automation tools VCG(Verification Condition Generator)and Isabelle are used to improve the automation of formal verification.An example of a stock’s maximum income demonstrates the effectiveness of the proposed model.Furthermore,the proposed model has some relevance for automatic software generation.
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The principal-subordinate hierarchical multi-objective programming model of initial water rights allocation was developed based on the principle of coordinated and sustainable development of different regions and water sectors within a basin. With the precondition of strictly controlling maximum emissions rights, initial water rights were allocated between the first and the second levels of the hierarchy in order to promote fair and coordinated development across different regions of the basin and coordinated and efficient water use across different water sectors, realize the maximum comprehensive benefits to the basin, promote the unity of quantity and quality of initial water rights allocation, and eliminate water conflict across different regions and water sectors. According to interactive decision-making theory, a principal-subordinate hierarchical interactive iterative algorithm based on the satisfaction degree was developed and used to solve the initial water rights allocation model. A case study verified the validity of the model.
基金Project(2014BAG01B0403)supported by the High-Tech Research and Development Program of China
文摘In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.
文摘A quadratic programming model is established to choose the blocks to be blasted in a given period. The length of this period depends on the production planning requirements. During the given period, the blocks' parameters are available from the geological database of the mine. The objective is to minimize the deviation of the average ore grade of blasted blocks from the standard ore grade required by the mill. Transportation ability constraint. production quantity demand constraint. minimum safety bench constraint. block size constraint and block, bench precedence constraints are considered in forming the programming model. This model has more practical objective function and reasonable constraints compared with the existing model for this kind of problems.
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The refugee immigration problem can be considered as a special “transportation problem”. Linear Programming Model is built, where two objectives with weight in the objective function, for the shortest routes that the refugees go along and the minimum number of refugees stayed in each country. An example of EU is introduced and calculated on Lingo software. The results show that the model is available to solve the refugee immigration problem in different scale.
文摘As one part of the Landstad International Metropolitan Area,Utrecht has become known as one of the best tourist destinations in recent years,with the rapid growth of worldwide travel trends.In this paper,through the adaption of the linear programming model,the paper intends to not only quantify the optimum number of visitors to Utrecht but also formulate a number of policy recommendations based on the reconstruction of this optimum.The paper draws the following conclusions:(1) tourist carrying capacity of Utrecht is not yet exceeded;(2) restrictive accommodation policy does not currently seem necessary;(3) the cultural-historical attractions are not yet optimally used;(4) investing in strategic provisions is currently not necessary.And from the conclusion,the paper further puts forward the following suggestions on the city’s tourism development strategy:(1) to identify "tourist flood plains";(2) to encourage the tourist disclosure of these alternatives;(3) to invest even more explicitly in residential tourism and,where possible,curb day tourism;(4) to introduce a new business model.
基金funded by the National Institute for Occupational Health and Safety under grant U60OH012351an Artificially Intelligent Mining Systems(AIMS)Capacity Building Project under contract number 75D30119C06044 for safer and healthier automated operations.
文摘Ensuring the safe evacuation of miners during fire emergencies in the shortest possible time is one of the most critical aspects of underground mining operations.Despite advances in mining evacuation methods,little research has been conducted on mine vehicles in this context.This study proposed a vehicle-augmented evacuation integer programming(VEIP)model to minimize the total evacuation cost as a function of the required evacuation time during fire emergencies.This approach aims to minimize the risk of miners being exposed to dangerous fire conditions by strategically integrating mine vehicles into the evacuation procedure.The approach determines the optimal evacuation path for each miner,considering factors such as available mine vehicles,miners’locations,refuge chambers,and fresh-air bases.To validate the effectiveness of the developed VEIP model,a case study was conducted using the mine layout of the Turquoise Ridge Underground Mine in the United States.Furthermore,a statistical comparison was conducted between the VEIP model and the evacuation integer programming(EIP)model,tailored to evacuation on foot,to emphasize vehicles’influence on the evacuation process.The results showed that integrating mine vehicles into evacuation procedures significantly reduces the total evacuation time.A cost savings analysis in the VEIP model revealed that the evacuation time savings increase exponentially as the number of miners present during evacuation increases.The potential benefits of using mine vehicles to improve the efficiency of evacuation from underground mine fires were highlighted in this study.
基金supported by the National Science Foundation for Distinguished Young Scholars of China(No.52425212)National Key Research and Development Program of China(No.2021YFA0717100)National Natural Science Foundation of China(Nos.12072270,U2013206,and 52442214).
文摘To establish the optimal reference trajectory for a near-space vehicle under free terminal time,a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization.First,the model predictive static programming method is developed by incorporating neighboring terms and trust region,enabling rapid generation of precise optimal solutions.Next,an adaptive fish swarm optimization technique is employed to identify a sub-optimal solution,while a momentum gradient descent method with learning rate decay ensures the convergence to the global optimal solution.To validate the feasibility and accuracy of the proposed method,a near-space vehicle example is analyzed and simulated during its glide phase.The simulation results demonstrate that the proposed method aligns with theoretical derivations and outperforms existing methods in terms of convergence speed and accuracy.Therefore,the proposed method offers significant practical value for solving the fast trajectory optimization problem in near-space vehicle applications.
文摘This study embarks on a comprehensive examination of optimization techniques within GPU-based parallel programming models,pivotal for advancing high-performance computing(HPC).Emphasizing the transition of GPUs from graphic-centric processors to versatile computing units,it delves into the nuanced optimization of memory access,thread management,algorithmic design,and data structures.These optimizations are critical for exploiting the parallel processing capabilities of GPUs,addressingboth the theoretical frameworks and practical implementations.By integrating advanced strategies such as memory coalescing,dynamic scheduling,and parallel algorithmic transformations,this research aims to significantly elevate computational efficiency and throughput.The findings underscore the potential of optimized GPU programming to revolutionize computational tasks across various domains,highlighting a pathway towards achieving unparalleled processing power and efficiency in HPC environments.The paper not only contributes to the academic discourse on GPU optimization but also provides actionable insights for developers,fostering advancements in computational sciences and technology.
基金partially supported by the National Natural Science Foundation of China under Grant No.62225206.
文摘Unified programming models can effectively improve program portability on various heterogeneous high-performance computers.Existing unified programming models put a lot of effort to code portability but are still far from achieving good performance portability.In this paper,we present a preliminary design of a performance-portable unified programming model including four aspects:programming language,programming abstraction,compilation optimization,and scheduling system.Specifically,domain-specific languages introduce domain knowledge to decouple the optimizations for different applications and architectures.The unified programming abstraction unifies the common features of different architectures to support common optimizations.Multi-level compilation optimization enables comprehensive performance optimization based on multi-level intermediate representations.Resource-aware lightweight runtime scheduling system improves the resource utilization of heterogeneous computers.This is a perspective paper to show our viewpoints on programming models for emerging heterogeneous systems.
基金Project (Nos. 60174009 and 70071017) supported by the NationalNatural Science Foundation of China
文摘This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.
基金This work is supported by the National Research Foundation,Prime Ministers Office,Singapore under its Campus for Research Excellence and Technological Enterprise(CREATE)programme,and by the Energy and Environmental Sustainability for Megacities(E2S2)Phase II program of the National Research Foundation,Prime Ministers Office,Singapore under its CREATE programme。
文摘This study combines multi-regional inputoutput(MRIO)model with linear programming(LP)model to explore economic structure adjustment strategies for the reduction of carbon dioxide(CO_(2))emissions.A particular feature of this study is the identification of the optimal regulation sequence of final products in various regions to reduce CO_(2)emissions with the minimum loss in gross domestic product(GDP).By using China's MRIO tables 2017 with 28 regions and 42 economic sectors,results show that reduction in final demand leads to simultaneous reductions in GDP and CO_(2)emissions.Nevertheless,certain demand side regulation strategy can be adopted to lower CO_(2)emissions at the smallest loss of economic growth.Several key final products,such as metallurgy,nonmetal,metal,and chemical products,should first be regulated to reduce CO_(2)emissions at the minimum loss in GDP.Most of these key products concentrate in the coastal developed regions in China.The proposed MRIO-LP model considers the inter-relationship among various sectors and regions,and can aid policy makers in designing effective policy for industrial structure adjustment at the regional level to achieve the national environmental and economic targets.
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This paper presents a self-contained proof of Special Termination of MMP (Minimal Model Program). By refining the assumptions and simplifying the argument, it offers a more accessible approach compared to the original proof in BCHM (Birkar-Cascini-Hacon-McKernan).
文摘Plant invasion refers to the phenomenon that some plants grow too fast due to they are far away from the original living environment or predators, affecting the local environment. With the development of tourism and trade, the harm caused by invasive plants will be more and more serious. Therefore, it is necessary to ex- plore an effective method for controlling plant invasion through qualitative and quan- titative research. In this paper, the models were established for the early and late harmful plant invasion control. The huge computation was completed by the com- puter programming to obtain the optimal solutions of the models. The real meaning of the optimal solution was further discussed. Through numerical simulations and discussion, it could be concluded that the quantitative research on the invasive plant control had a certain application value.
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
