With the development of technology,diffusion model-based solvers have shown significant promise in solving Combinatorial Optimization(CO)problems,particularly in tackling Non-deterministic Polynomial-time hard(NP-hard...With the development of technology,diffusion model-based solvers have shown significant promise in solving Combinatorial Optimization(CO)problems,particularly in tackling Non-deterministic Polynomial-time hard(NP-hard)problems such as the Traveling Salesman Problem(TSP).However,existing diffusion model-based solvers typically employ a fixed,uniform noise schedule(e.g.,linear or cosine annealing)across all training instances,failing to fully account for the unique characteristics of each problem instance.To address this challenge,we present GraphGuided Diffusion Solvers(GGDS),an enhanced method for improving graph-based diffusion models.GGDS leverages Graph Neural Networks(GNNs)to capture graph structural information embedded in node coordinates and adjacency matrices,dynamically adjusting the noise levels in the diffusion model.This study investigates the TSP by examining two distinct time-step noise generation strategies:cosine annealing and a Neural Network(NN)-based approach.We evaluate their performance across different problem scales,particularly after integrating graph structural information.Experimental results indicate that GGDS outperforms previous methods with average performance improvements of 18.7%,6.3%,and 88.7%on TSP-500,TSP-100,and TSP-50,respectively.Specifically,GGDS demonstrates superior performance on TSP-500 and TSP-50,while its performance on TSP-100 is either comparable to or slightly better than that of previous methods,depending on the chosen noise schedule and decoding strategy.展开更多
This study examines the mediating role of positive psychological capital and the moderating role of ethnicity in the relationship between mindfulness and internalizing/externalizing problems among adolescents.The stud...This study examines the mediating role of positive psychological capital and the moderating role of ethnicity in the relationship between mindfulness and internalizing/externalizing problems among adolescents.The study sample comprized Chinese adolescents(N=637 ethnic minority;females=40.97%,meam age=12.68,SD=0.49 years;N=636 Han;females=49.06%,mean age=12.71,SD=0.47 years).The participants completed the Child and Adolescent Mindfulness Measure,the Positive Psycap Questionnaire,and the Youth Self-Report.Results from the moderated mediation analysis showed mindfulness was negatively associated with both internalizing and externalizing problems.Ethnicity moderated the relationship between mindfulness and internalizing problems to be stronger for Han adolescents compared to ethnic minority adolescents.Psychological capital mediated the relationship between mindfulness and internalizing problems in both groups,with a negative direction.Findings support the Conservation of Resources theory and highlight mindfulness as a personal resource fostering adolescent well-being in multicultural contexts.展开更多
Generalised reduced masses with a set of equations governing the three relative motions between two of 3-bodies in their gravitational field are established,of which the dynamic characteristics of 3-body dynamics,fund...Generalised reduced masses with a set of equations governing the three relative motions between two of 3-bodies in their gravitational field are established,of which the dynamic characteristics of 3-body dynamics,fundamental bases of this paper,are revealed.Based on these findings,an equivalent system is developed,which is a 2-body system with its total mass,constant angular momentum,kinetic and potential energies same as the total ones of three relative motions,so that it can be solved using the well-known theory of the 2-body system.From the solution of an equivalent system with the revealed characteristics of three relative motions,the general theoretical solutions of the 3-body system are obtained in the curve-integration forms along the orbits in the imaged radial motion space.The possible periodical orbits with generalised Kepler’s law are presented.Following the description and mathematical demonstrations of the proposed methods,the examples including Euler’s/Lagrange’s problems,and a reported numerical one are solved to validate the proposed methods.The methods derived from the 3-body system are extended to N-body problems.展开更多
The proliferation of carrier aircraft and the integration of unmanned aerial vehicles(UAVs)on aircraft carriers present new challenges to the automation of launch and recovery operations.This paper investigates a coll...The proliferation of carrier aircraft and the integration of unmanned aerial vehicles(UAVs)on aircraft carriers present new challenges to the automation of launch and recovery operations.This paper investigates a collaborative scheduling problem inherent to the operational processes of carrier aircraft,where launch and recovery tasks are conducted concurrently on the flight deck.The objective is to minimize the cumulative weighted waiting time in the air for recovering aircraft and the cumulative weighted delay time for launching aircraft.To tackle this challenge,a multiple population self-adaptive differential evolution(MPSADE)algorithm is proposed.This method features a self-adaptive parameter updating mechanism that is contingent upon population diversity,an asynchronous updating scheme,an individual migration operator,and a global crossover mechanism.Additionally,comprehensive experiments are conducted to validate the effectiveness of the proposed model and algorithm.Ultimately,a comparative analysis with existing operation modes confirms the enhanced efficiency of the collaborative operation mode.展开更多
Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recov...Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery. We first derive the projection formulas for a vector onto the feasible sets. The centralized circumcentered-reflection method is designed to solve the convex feasibility problem. Some numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm, showing superior performance compared to conventional alternating projection methods.展开更多
During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.展开更多
Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when ta...Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.展开更多
The newly formulated non-Newtonian rivulet flows streaming down an inclined planar surface,with additional periodic perturbations arising from the application of the 2nd Stokes problem to the investigation of rivulet ...The newly formulated non-Newtonian rivulet flows streaming down an inclined planar surface,with additional periodic perturbations arising from the application of the 2nd Stokes problem to the investigation of rivulet dynamics,are demonstrated in the current research.Hereby,the 2nd Stokes problem assumes that the surface,with a thin shared layer of the fluid on it,oscillates in a harmonic manner along the x-axis of the rivulet flow,which coincides with the main flow direction streaming down the underlying surface.We obtain the exact extension of the rivulet flow family,clarifying the structure of the pressure field,which fully absorbs the arising perturbation.The profile of the velocity field is assumed to be Gaussian-type with a non-zero level of plasticity.Hence,the absolutely non-Newtonian case of the viscoplastic flow solution,which satisfies the motion and continuity equations,is considered(with particular cases of exact solutions for pressure).The perturbed governing equations of motion for rivulet flows then result in the Riccati-type ordinary differential equation(ODE),describing the dynamics of the coordinate x(t).The approximated schematic dynamics are presented in graphical plots.展开更多
This study proposes a class of augmented subspace schemes for the weak Galerkin(WG)finite element method used to solve eigenvalue problems.The augmented subspace is built with the conforming linear finite element spac...This study proposes a class of augmented subspace schemes for the weak Galerkin(WG)finite element method used to solve eigenvalue problems.The augmented subspace is built with the conforming linear finite element space defined on the coarse mesh and the eigen-function approximations in the WG finite element space defined on the fine mesh.Based on this augmented subspace,solving the eigenvalue problem in the fine WG finite element space can be reduced to the solution of the linear boundary value problem in the same WG finite element space and a low dimensional eigenvalue problem in the augmented sub-space.The proposed augmented subspace techniques have the second order convergence rate with respect to the coarse mesh size,as demonstrated by the accompanying error esti-mates.Finally,a few numerical examples are provided to validate the proposed numerical techniques.展开更多
The paper presents a novel quantum method for addressing two fundamental routing problems:the Traveling Salesman Problem(TSP)and theVehicle Routing Problem(VRP),both central to routing challenges.The proposed method,n...The paper presents a novel quantum method for addressing two fundamental routing problems:the Traveling Salesman Problem(TSP)and theVehicle Routing Problem(VRP),both central to routing challenges.The proposed method,named the Indirect Quantum Approximate Optimization Algorithm(IQAOA),leverages an indirect solution representation using ranking.Our contribution focuses on two main areas:1)the indirect representation of solutions,and 2)the integration of this representation into an extended version of QAOA,called IQAOA.This approach offers an alternative to QAOA and includes the following components:1)a quantum parameterized circuit designed to simulate string vectors on a quantum processor,2)a classical meta-optimization method executed on a classical computer,and 3)the computation of the average cost for each string vector,achieved through a well-established algorithm from the operations research community tailored to the specific problem.IQAOA provides an efficient means to address quantum optimization problems by combining quantum and classical computation methods.Its primary advantage lies in deriving a quantum circuit that requires significantly fewer gates,making it suitable for execution on current noisy quantum computing platforms.Through numerical experiments employing IQAOA,we successfully solved instances of the 10-customer Traveling Salesman Problem(TSP)using the IBM simulator.To our knowledge,this is the largest application of a QAOA-based approach to solving the TSP.Additionally,IQAOA enables the resolution of the Vehicle Routing Problem(VRP)by leveraging the Split algorithm,which transforms a TSP permutation into a corresponding VRP solution.展开更多
The Orlicz Minkowski problem for logarithmic capacity seeks to determine the necessary and sufficient conditions for a given finite Borel measure,such that it is the Orlicz logarithmic capacitary measure of a convex b...The Orlicz Minkowski problem for logarithmic capacity seeks to determine the necessary and sufficient conditions for a given finite Borel measure,such that it is the Orlicz logarithmic capacitary measure of a convex body.The Orlicz Minkowski problem for loga-rithmic capacity includes the Minkowski problem for logarithmic capacity and the Lp Minkowski problem for logarithmic capacity as special cases.The discrete case has been solved by the researchers.In this paper,we solve the Orlicz Minkowski problem for logarithmic capacity with respect to general Borel measures by applying an approximation scheme.展开更多
基金supported by the National Science and Technology Council,Taiwan,under grant no.NSTC 114-2221-E-197-005-MY3.
文摘With the development of technology,diffusion model-based solvers have shown significant promise in solving Combinatorial Optimization(CO)problems,particularly in tackling Non-deterministic Polynomial-time hard(NP-hard)problems such as the Traveling Salesman Problem(TSP).However,existing diffusion model-based solvers typically employ a fixed,uniform noise schedule(e.g.,linear or cosine annealing)across all training instances,failing to fully account for the unique characteristics of each problem instance.To address this challenge,we present GraphGuided Diffusion Solvers(GGDS),an enhanced method for improving graph-based diffusion models.GGDS leverages Graph Neural Networks(GNNs)to capture graph structural information embedded in node coordinates and adjacency matrices,dynamically adjusting the noise levels in the diffusion model.This study investigates the TSP by examining two distinct time-step noise generation strategies:cosine annealing and a Neural Network(NN)-based approach.We evaluate their performance across different problem scales,particularly after integrating graph structural information.Experimental results indicate that GGDS outperforms previous methods with average performance improvements of 18.7%,6.3%,and 88.7%on TSP-500,TSP-100,and TSP-50,respectively.Specifically,GGDS demonstrates superior performance on TSP-500 and TSP-50,while its performance on TSP-100 is either comparable to or slightly better than that of previous methods,depending on the chosen noise schedule and decoding strategy.
基金supported by the Guizhou Provincial Science and Technology Projects[Basic Science of Guizhou-[2024]Youth 309,Guizhou Platform Talents[2021]1350-046]Zunyi Science and Technology Cooperation[HZ(2024)311]+3 种基金Funding of the Chinese Academy of Social Sciences(2024SYZH005)Peking University Longitudinal Scientific Research Technical Service Project(G-252)Guizhou Provincial Graduate Student Research Fund Project(2024YJSKYJJ339)Zunyi Medical University Graduate Research Fund Project(ZYK206).
文摘This study examines the mediating role of positive psychological capital and the moderating role of ethnicity in the relationship between mindfulness and internalizing/externalizing problems among adolescents.The study sample comprized Chinese adolescents(N=637 ethnic minority;females=40.97%,meam age=12.68,SD=0.49 years;N=636 Han;females=49.06%,mean age=12.71,SD=0.47 years).The participants completed the Child and Adolescent Mindfulness Measure,the Positive Psycap Questionnaire,and the Youth Self-Report.Results from the moderated mediation analysis showed mindfulness was negatively associated with both internalizing and externalizing problems.Ethnicity moderated the relationship between mindfulness and internalizing problems to be stronger for Han adolescents compared to ethnic minority adolescents.Psychological capital mediated the relationship between mindfulness and internalizing problems in both groups,with a negative direction.Findings support the Conservation of Resources theory and highlight mindfulness as a personal resource fostering adolescent well-being in multicultural contexts.
文摘Generalised reduced masses with a set of equations governing the three relative motions between two of 3-bodies in their gravitational field are established,of which the dynamic characteristics of 3-body dynamics,fundamental bases of this paper,are revealed.Based on these findings,an equivalent system is developed,which is a 2-body system with its total mass,constant angular momentum,kinetic and potential energies same as the total ones of three relative motions,so that it can be solved using the well-known theory of the 2-body system.From the solution of an equivalent system with the revealed characteristics of three relative motions,the general theoretical solutions of the 3-body system are obtained in the curve-integration forms along the orbits in the imaged radial motion space.The possible periodical orbits with generalised Kepler’s law are presented.Following the description and mathematical demonstrations of the proposed methods,the examples including Euler’s/Lagrange’s problems,and a reported numerical one are solved to validate the proposed methods.The methods derived from the 3-body system are extended to N-body problems.
文摘The proliferation of carrier aircraft and the integration of unmanned aerial vehicles(UAVs)on aircraft carriers present new challenges to the automation of launch and recovery operations.This paper investigates a collaborative scheduling problem inherent to the operational processes of carrier aircraft,where launch and recovery tasks are conducted concurrently on the flight deck.The objective is to minimize the cumulative weighted waiting time in the air for recovering aircraft and the cumulative weighted delay time for launching aircraft.To tackle this challenge,a multiple population self-adaptive differential evolution(MPSADE)algorithm is proposed.This method features a self-adaptive parameter updating mechanism that is contingent upon population diversity,an asynchronous updating scheme,an individual migration operator,and a global crossover mechanism.Additionally,comprehensive experiments are conducted to validate the effectiveness of the proposed model and algorithm.Ultimately,a comparative analysis with existing operation modes confirms the enhanced efficiency of the collaborative operation mode.
基金Supported by the Natural Science Foundation of Guangxi Province(Grant Nos.2023GXNSFAA026067,2024GXN SFAA010521)the National Natural Science Foundation of China(Nos.12361079,12201149,12261026).
文摘Convex feasibility problems are widely used in image reconstruction, sparse signal recovery, and other areas. This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery. We first derive the projection formulas for a vector onto the feasible sets. The centralized circumcentered-reflection method is designed to solve the convex feasibility problem. Some numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm, showing superior performance compared to conventional alternating projection methods.
基金supported by the National Natural Sci‐ence Foundation of China(Grant No.62306325)。
文摘During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.
基金funded by National Natural Science Foundation of China(Nos.12402142,11832013 and 11572134)Natural Science Foundation of Hubei Province(No.2024AFB235)+1 种基金Hubei Provincial Department of Education Science and Technology Research Project(No.Q20221714)the Opening Foundation of Hubei Key Laboratory of Digital Textile Equipment(Nos.DTL2023019 and DTL2022012).
文摘Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.
文摘The newly formulated non-Newtonian rivulet flows streaming down an inclined planar surface,with additional periodic perturbations arising from the application of the 2nd Stokes problem to the investigation of rivulet dynamics,are demonstrated in the current research.Hereby,the 2nd Stokes problem assumes that the surface,with a thin shared layer of the fluid on it,oscillates in a harmonic manner along the x-axis of the rivulet flow,which coincides with the main flow direction streaming down the underlying surface.We obtain the exact extension of the rivulet flow family,clarifying the structure of the pressure field,which fully absorbs the arising perturbation.The profile of the velocity field is assumed to be Gaussian-type with a non-zero level of plasticity.Hence,the absolutely non-Newtonian case of the viscoplastic flow solution,which satisfies the motion and continuity equations,is considered(with particular cases of exact solutions for pressure).The perturbed governing equations of motion for rivulet flows then result in the Riccati-type ordinary differential equation(ODE),describing the dynamics of the coordinate x(t).The approximated schematic dynamics are presented in graphical plots.
基金partly supported by the Beijing Natural Science Foundation(Grant No.Z200003)by the National Natural Science Foundation of China(Grant Nos.12331015,12301475,12301465)+1 种基金by the National Center for Mathematics and Interdisciplinary Science,Chinese Academy of Sciencesby the Research Foundation for the Beijing University of Technology New Faculty(Grant No.006000514122516).
文摘This study proposes a class of augmented subspace schemes for the weak Galerkin(WG)finite element method used to solve eigenvalue problems.The augmented subspace is built with the conforming linear finite element space defined on the coarse mesh and the eigen-function approximations in the WG finite element space defined on the fine mesh.Based on this augmented subspace,solving the eigenvalue problem in the fine WG finite element space can be reduced to the solution of the linear boundary value problem in the same WG finite element space and a low dimensional eigenvalue problem in the augmented sub-space.The proposed augmented subspace techniques have the second order convergence rate with respect to the coarse mesh size,as demonstrated by the accompanying error esti-mates.Finally,a few numerical examples are provided to validate the proposed numerical techniques.
文摘The paper presents a novel quantum method for addressing two fundamental routing problems:the Traveling Salesman Problem(TSP)and theVehicle Routing Problem(VRP),both central to routing challenges.The proposed method,named the Indirect Quantum Approximate Optimization Algorithm(IQAOA),leverages an indirect solution representation using ranking.Our contribution focuses on two main areas:1)the indirect representation of solutions,and 2)the integration of this representation into an extended version of QAOA,called IQAOA.This approach offers an alternative to QAOA and includes the following components:1)a quantum parameterized circuit designed to simulate string vectors on a quantum processor,2)a classical meta-optimization method executed on a classical computer,and 3)the computation of the average cost for each string vector,achieved through a well-established algorithm from the operations research community tailored to the specific problem.IQAOA provides an efficient means to address quantum optimization problems by combining quantum and classical computation methods.Its primary advantage lies in deriving a quantum circuit that requires significantly fewer gates,making it suitable for execution on current noisy quantum computing platforms.Through numerical experiments employing IQAOA,we successfully solved instances of the 10-customer Traveling Salesman Problem(TSP)using the IBM simulator.To our knowledge,this is the largest application of a QAOA-based approach to solving the TSP.Additionally,IQAOA enables the resolution of the Vehicle Routing Problem(VRP)by leveraging the Split algorithm,which transforms a TSP permutation into a corresponding VRP solution.
基金Supported by Postgraduate Scientific Research Innovation Project of Hunan Province(CX20231033)Science and Technology Research Project of Jiangxi Provincial Education Department(GJJ210815)+2 种基金Jiangxi Provincial Natural Science Foundation(20232BAB201005)the National Natural Science Founda-tion of China(12461010,12161043)the Scientific Research Fund of Hunan Provincial Education Department(24A0338)。
文摘The Orlicz Minkowski problem for logarithmic capacity seeks to determine the necessary and sufficient conditions for a given finite Borel measure,such that it is the Orlicz logarithmic capacitary measure of a convex body.The Orlicz Minkowski problem for loga-rithmic capacity includes the Minkowski problem for logarithmic capacity and the Lp Minkowski problem for logarithmic capacity as special cases.The discrete case has been solved by the researchers.In this paper,we solve the Orlicz Minkowski problem for logarithmic capacity with respect to general Borel measures by applying an approximation scheme.
