Formalizing complex processes and phenomena of a real-world problem may require a large number of variables and constraints,resulting in what is termed a large-scale optimization problem.Nowadays,such large-scale opti...Formalizing complex processes and phenomena of a real-world problem may require a large number of variables and constraints,resulting in what is termed a large-scale optimization problem.Nowadays,such large-scale optimization problems are solved using computing machines,leading to an enormous computational time being required,which may delay deriving timely solutions.Decomposition methods,which partition a large-scale optimization problem into lower-dimensional subproblems,represent a key approach to addressing time-efficiency issues.There has been significant progress in both applied mathematics and emerging artificial intelligence approaches on this front.This work aims at providing an overview of the decomposition methods from both the mathematics and computer science points of view.We also remark on the state-of-the-art developments and recent applications of the decomposition methods,and discuss the future research and development perspectives.展开更多
Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynam...Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.展开更多
The Traveling Salesman Problem(TSP)is a well-known NP-Hard problem,particularly challenging for conventional solving methods due to the curse of dimensionality in high-dimensional instances.This paper proposes a novel...The Traveling Salesman Problem(TSP)is a well-known NP-Hard problem,particularly challenging for conventional solving methods due to the curse of dimensionality in high-dimensional instances.This paper proposes a novel Double-stage Surrogate-assisted Pigeon-inspired Optimization algorithm(DOSA-PIO)to address this issue.DOSA-PIO integrates the ordering points to identify the clustering structure method for data clustering and employs a local surrogate model to assist the evolution of the Pigeon-inspired Optimization(PIO)algorithm.This combination enhances the algorithm’s ability to explore the solution space and converge to optimal solutions more effectively.Additionally,two novel approaches are introduced to extend the generalizability of continuous algorithms for solving discrete problems,enabling the adaptation of continuous optimization techniques to the discrete nature of TSP.Extensive experiments using benchmark functions and high-dimensional TSP instances demonstrate that DOSA-PIO significantly outperforms comparative algorithms in various dimensions(10D,20D,30D,50D,and 100D).The proposed algorithm provides superior solutions compared to traditional methods,highlighting its potential for solving high-dimensional TSPs.By leveraging advanced data clustering techniques and surrogate-assisted optimization,DOSA-PIO offers an effective solution for high-dimensional TSP instances,with experimental results confirming its superior performance and potential for practical applications in complex optimization problems.展开更多
Unmanned Aerial Vehicle(UAV)stands as a burgeoning electric transportation carrier,holding substantial promise for the logistics sector.A reinforcement learning framework Centralized-S Proximal Policy Optimization(C-S...Unmanned Aerial Vehicle(UAV)stands as a burgeoning electric transportation carrier,holding substantial promise for the logistics sector.A reinforcement learning framework Centralized-S Proximal Policy Optimization(C-SPPO)based on centralized decision process and considering policy entropy(S)is proposed.The proposed framework aims to plan the best scheduling scheme with the objective of minimizing both the timeout of order requests and the flight impact of UAVs that may lead to conflicts.In this framework,the intents of matching act are generated through the observations of UAV agents,and the ultimate conflict-free matching results are output under the guidance of a centralized decision maker.Concurrently,a pre-activation operation is introduced to further enhance the cooperation among UAV agents.Simulation experiments based on real-world data from New York City are conducted.The results indicate that the proposed CSPPO outperforms the baseline algorithms in the Average Delay Time(ADT),the Maximum Delay Time(MDT),the Order Delay Rate(ODR),the Average Flight Distance(AFD),and the Flight Impact Ratio(FIR).Furthermore,the framework demonstrates scalability to scenarios of different sizes without requiring additional training.展开更多
As power systems expand,solving the unit commitment problem(UCP)becomes increasingly challenging due to the curse of dimensionality,and traditional methods often struggle to balance computational efficiency and soluti...As power systems expand,solving the unit commitment problem(UCP)becomes increasingly challenging due to the curse of dimensionality,and traditional methods often struggle to balance computational efficiency and solution optimality.To tackle this issue,we propose a problem-structure-informed quantum approximate optimization algorithm(QAOA)framework that fully exploits the quantum advantage under extremely limited quantum resources.Specifically,we leverage the inherent topological structure of power systems to decompose large-scale UCP instances into smaller subproblems,which are solvable in parallel by limited number of qubits.This decomposition not only circumvents the current hardware limitations of quantum computing but also achieves higher performance as the graph structure of the power system becomes more sparse.Consequently,our approach can be extended to future power systems that are larger and more complex.展开更多
To solve large-scale optimization problems,Fragrance coefficient and variant Particle Swarm local search Butterfly Optimization Algorithm(FPSBOA)is proposed.In the position update stage of Butterfly Optimization Algor...To solve large-scale optimization problems,Fragrance coefficient and variant Particle Swarm local search Butterfly Optimization Algorithm(FPSBOA)is proposed.In the position update stage of Butterfly Optimization Algorithm(BOA),the fragrance coefficient is designed to balance the exploration and exploitation of BOA.The variant particle swarm local search strategy is proposed to improve the local search ability of the current optimal butterfly and prevent the algorithm from falling into local optimality.192000-dimensional functions and 201000-dimensional CEC 2010 large-scale functions are used to verify FPSBOA for complex large-scale optimization problems.The experimental results are statistically analyzed by Friedman test and Wilcoxon rank-sum test.All attained results demonstrated that FPSBOA can better solve more challenging scientific and industrial real-world problems with thousands of variables.Finally,four mechanical engineering problems and one ten-dimensional process synthesis and design problem are applied to FPSBOA,which shows FPSBOA has the feasibility and effectiveness in real-world application problems.展开更多
Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to tr...Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.展开更多
A modified bottleneck-based （MB） heuristic for large-scale job-shop scheduling problems with a welldefined bottleneck is suggested, which is simpler but more tailored than the shifting bottleneck （SB） procedure. I...A modified bottleneck-based （MB） heuristic for large-scale job-shop scheduling problems with a welldefined bottleneck is suggested, which is simpler but more tailored than the shifting bottleneck （SB） procedure. In this algorithm, the bottleneck is first scheduled optimally while the non-bottleneck machines are subordinated around the solutions of the bottleneck schedule by some effective dispatching rules. Computational results indicate that the MB heuristic can achieve a better tradeoff between solution quality and computational time compared to SB procedure for medium-size problems. Furthermore, it can obtain a good solution in a short time for large-scale jobshop scheduling problems.展开更多
1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Int...1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.展开更多
The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,...The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,in combination with numerical simulation,was conducted to investigate the influence of ground fissures on a metro shield tunnel.The results indicate that the lining contact pressure at the vault increases in the hanging wall while decreases in the footwall,resulting in a two-dimensional stress state of vertical shear and axial tension-compression,and simultaneous vertical dislocation and axial tilt for the segments around the ground fissure.In addition,the damage to curved bolts includes tensile yield,flexural yield,and shear twist,leading to obvious concrete lining damage,particularly at the vault,arch bottom,and hance,indicating that the joints in these positions are weak areas.The shield tunnel orthogonal to the ground fissure ultimately experiences shear failure,suggesting that the maximum actual dislocation of ground fissure that the structure can withstand is approximately 20 cm,and five segment rings in the hanging wall and six segment rings in the footwall also need to be reinforced.This study could provide a reference for metro design in ground fissure sites.展开更多
Based on the analysis of typical lacustrine shale oil zones in China and their geological characteristics,this study elucidates the fundamental differences between the enrichment patterns of shale oil sweet spots and ...Based on the analysis of typical lacustrine shale oil zones in China and their geological characteristics,this study elucidates the fundamental differences between the enrichment patterns of shale oil sweet spots and conventional oil and gas.The key parameters and evaluation methods for assessing the large-scale production potential of lacustrine shale oil are proposed.The results show that shale oil is a petroleum resource that exists in organic-rich shale formations,in other words,it is preserved in its source bed,following a different process of generation-accumulation-enrichment from conventional oil and gas.Thus,the concept of“reservoir”seems to be inapplicable to shale oil.In China,lacustrine shale oil is distributed widely,but the geological characteristics and sweet spots enrichment patterns of shale oil vary significantly in lacustrine basins where the water environment and the tectonic evolution and diagenetic transformation frameworks are distinct.The core of the evaluation of lacustrine shale oil is“sweet spot volume”.The key factors for evaluating the large-scale production of continental shale oil are the oil storage capacity,oil-bearing capacity and oil producing capacity.The key parameters for evaluating these capacities are total porosity,oil content,and free oil content,respectively.It is recommended to determine the total porosity of shale by combining helium porosity measurement with nuclear magnetic resonance(NMR)method,the oil content of key layers by using organic solvent extraction,NMR method and high pressure mercury intrusion methods,and the free oil content by using NMR fluid distribution secondary spectral stripping decomposition and logging.The research results contribute supplemental insights on continental shale oil deliverability in China,and provide a scientific basis for the rapid exploration and large-scale production of lacustrine shale oil.展开更多
The performance of analytical derivative and sparse matrix techniques applied to a traditional dense sequential quadratic programming (SQP) is studied, and the strategy utilizing those techniques is also presented.Com...The performance of analytical derivative and sparse matrix techniques applied to a traditional dense sequential quadratic programming (SQP) is studied, and the strategy utilizing those techniques is also presented.Computational results on two typical chemical optimization problems demonstrate significant enhancement in efficiency, which shows this strategy is promising and suitable for large-scale process optimization problems.展开更多
The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the...The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the forging process.Using the previously optimized shape and initial position of preform,the influence of the friction condition(friction factor m=0.1–0.3)on material flow and cavity filling was studied by numerical method with a shear friction model.A novel filling index was defined to reflect material flow into left and right flashes and zoom in on friction-induced results.The results indicate that the workpiece moves rigidly to the right direction,with the displacement decreasing as m increases.When m<0.18,the underfilling defect will occur in the left side of strut forging,while overflow occurs in the right forging die cavity.By combining the filling index and analyses of material flow and filling status,a reasonable friction factor interval of m=0.21–0.24 can be determined.Within this interval,the cavity filling behavior demonstrates robustness,with friction fluctuations exerting minimal influence.展开更多
Based on questionnaire surveys and field interviews conducted with various types of agricultural production organizations across five districts and four counties in Daqing City,this study combines relevant theoretical...Based on questionnaire surveys and field interviews conducted with various types of agricultural production organizations across five districts and four counties in Daqing City,this study combines relevant theoretical frameworks to systematically examine the evolution,performance,and influencing factors of governance mechanisms within these organizations.Using both quantitative and inductive analytical methods,the paper proposes innovative designs and supporting measures for improving governance mechanisms.The findings reveal that,amid large-scale farmland circulation,the governance mechanisms of agricultural production organizations in Daqing City are evolving from traditional to modern structures.However,challenges remain in areas such as decision-making efficiency,benefit distribution,and supervision mechanisms.In response,this study proposes innovative governance designs focusing on decision-making processes,profit-sharing mechanisms,and risk prevention.Corresponding policy recommendations are also provided to support the sustainable development of agricultural modernization in China.展开更多
This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management m...This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management measures.Through practical observation and logical analysis,this article elaborates on the management connotations of large-scale machinery and equipment in highway construction,affirming its management value from different perspectives.On this basis,it carefully analyzes the problems existing in the management of large-scale machinery and equipment,providing a detailed interpretation of issues such as the weak foundation of the equipment management system and the disconnection between equipment selection and configuration from reality.Combining the manifestations of related problems,this article proposes strategies such as strengthening the institutional foundation of equipment management,selecting and configuring equipment based on actual conditions,aiming to provide references for large-scale machinery and equipment management to relevant enterprises.展开更多
It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the ...It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.展开更多
Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by co...Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by conducting large-scale(1:13)experiments to investigate the scour hole pattern and equilibrium scour depth around both slender and large monopiles under irregular waves.The experiments adopted KeuleganeCarpenter number(NKC)values from 1.01 to 8.89 and diffraction parameter(D/L,where D is the diameter of the monopile,and L is the wave length)values from 0.016 to 0.056.The results showed that changes in the maximum scour location and scour hole shape around a slender monopile were associated with NKC,with differences observed between irregular and regular waves.Improving the calculation of NKC enhanced the accuracy of existing scour formulae under irregular waves.The maximum scour locations around a large monopile were consistently found on both sides,regardless of NKC and D/L,but the scour hole topography was influenced by both parameters.Notably,the scour range around a large monopile was at least as large as the monopile diameter.展开更多
In 2022, South China(SC) experienced record-breaking rainfall during its first rainy season, causing severe socioeconomic losses. This study examines the large-scale circulation anomalies responsible for this extreme ...In 2022, South China(SC) experienced record-breaking rainfall during its first rainy season, causing severe socioeconomic losses. This study examines the large-scale circulation anomalies responsible for this extreme event.Analysis reveals that the lower-tropospheric cyclonic anomaly over SC plays a crucial role. This cyclonic anomaly consists of extratropical northeasterly anomalies to the north of SC and tropical southwesterly anomalies to the south. Both components were particularly intense during the 2022 first rainy season, contributing to the heavy rainfall in SC. Moreover,the lower-tropospheric cyclonic anomaly is enhanced by its counterpart in the upper troposphere, which is associated with a wave train propagating from the North Atlantic to East Asia across the mid-high latitudes of the Eurasian continent.Further analysis indicates that the extratropical wave train correlates with sea surface temperature anomalies(SSTAs) in the North Atlantic. Additionally, the SSTAs over the North Indian Ocean also play a role in enhancing the tropical southwesterlies in the lower troposphere. This study highlights the combined influence of tropical and extratropical circulation anomalies, offering a comprehensive understanding of the record-breaking rainfall.展开更多
This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is...This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is placed on data acquisition and processing methods using total stations and automated monitoring systems.Through a comprehensive analysis of lateral,longitudinal,and vertical displacement data from 26 subgrade monitoring points,catenary columns,and track sections,this research evaluates how construction activities influence railway structures.The results show that displacement variations in the subgrades,catenary columns,and tracks remained within the established alert thresholds,exhibiting stable deformation trends and indicating that any adverse environmental impact was effectively contained.Furthermore,this paper proposes an early warning mechanism based on an automated monitoring system,which can promptly detect abnormal deformations and initiate emergency response procedures,thereby ensuring the safe operation of the railway.The integration of big data analysis and deformation prediction models offers a practical foundation for future safety management in railway construction.展开更多
The research on optimization methods for constellation launch deployment strategies focused on the consideration of mission interval time constraints at the launch site.Firstly,a dynamic modeling of the constellation ...The research on optimization methods for constellation launch deployment strategies focused on the consideration of mission interval time constraints at the launch site.Firstly,a dynamic modeling of the constellation deployment process was established,and the relationship between the deployment window and the phase difference of the orbit insertion point,as well as the cost of phase adjustment after orbit insertion,was derived.Then,the combination of the constellation deployment position sequence was treated as a parameter,together with the sequence of satellite deployment intervals,as optimization variables,simplifying a highdimensional search problem within a wide range of dates to a finite-dimensional integer programming problem.An improved genetic algorithm with local search on deployment dates was introduced to optimize the launch deployment strategy.With the new description of the optimization variables,the total number of elements in the solution space was reduced by N orders of magnitude.Numerical simulation confirms that the proposed optimization method accelerates the convergence speed from hours to minutes.展开更多
基金The Australian Research Council(DP200101197,DP230101107).
文摘Formalizing complex processes and phenomena of a real-world problem may require a large number of variables and constraints,resulting in what is termed a large-scale optimization problem.Nowadays,such large-scale optimization problems are solved using computing machines,leading to an enormous computational time being required,which may delay deriving timely solutions.Decomposition methods,which partition a large-scale optimization problem into lower-dimensional subproblems,represent a key approach to addressing time-efficiency issues.There has been significant progress in both applied mathematics and emerging artificial intelligence approaches on this front.This work aims at providing an overview of the decomposition methods from both the mathematics and computer science points of view.We also remark on the state-of-the-art developments and recent applications of the decomposition methods,and discuss the future research and development perspectives.
基金Supported by the National Natural Science Foundation of China(Nos.52293472,22473096 and 22471164)。
文摘Among various architectures of polymers,end-group-free rings have attracted growing interests due to their distinct physicochemical performances over the linear counterparts which are exemplified by reduced hydrodynamic size and slower degradation.It is key to develop facile methods to large-scale synthesis of polymer rings with tunable compositions and microstructures.Recent progresses in large-scale synthesis of polymer rings against single-chain dynamic nanoparticles,and the example applications in synchronous enhancing toughness and strength of polymer nanocomposites are summarized.Once there is the breakthrough in rational design and effective large-scale synthesis of polymer rings and their functional derivatives,a family of cyclic functional hybrids would be available,thus providing a new paradigm in developing polymer science and engineering.
基金funded by National Natural Science Foundation of China(Project No.52072314,52172321,52102391)China Shenhua Energy Co.,Ltd.,Science and Technology Program(Project No.GJNY-22-7)+2 种基金China State Railway Group Co.,Ltd.Science and Technology Program(P2022×013,K2023×030)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-131)the fundamental research funds for the central universities(2682022ZTPY068).
文摘The Traveling Salesman Problem(TSP)is a well-known NP-Hard problem,particularly challenging for conventional solving methods due to the curse of dimensionality in high-dimensional instances.This paper proposes a novel Double-stage Surrogate-assisted Pigeon-inspired Optimization algorithm(DOSA-PIO)to address this issue.DOSA-PIO integrates the ordering points to identify the clustering structure method for data clustering and employs a local surrogate model to assist the evolution of the Pigeon-inspired Optimization(PIO)algorithm.This combination enhances the algorithm’s ability to explore the solution space and converge to optimal solutions more effectively.Additionally,two novel approaches are introduced to extend the generalizability of continuous algorithms for solving discrete problems,enabling the adaptation of continuous optimization techniques to the discrete nature of TSP.Extensive experiments using benchmark functions and high-dimensional TSP instances demonstrate that DOSA-PIO significantly outperforms comparative algorithms in various dimensions(10D,20D,30D,50D,and 100D).The proposed algorithm provides superior solutions compared to traditional methods,highlighting its potential for solving high-dimensional TSPs.By leveraging advanced data clustering techniques and surrogate-assisted optimization,DOSA-PIO offers an effective solution for high-dimensional TSP instances,with experimental results confirming its superior performance and potential for practical applications in complex optimization problems.
基金the support of the Chinese Special Research Project for Civil Aircraft(No.MJZ17N22)the National Natural Science Foundation of China(Nos.U2133207,U2333214)+1 种基金the China Postdoctoral Science Foundation(No.2023M741687)the National Social Science Fund of China(No.22&ZD169)。
文摘Unmanned Aerial Vehicle(UAV)stands as a burgeoning electric transportation carrier,holding substantial promise for the logistics sector.A reinforcement learning framework Centralized-S Proximal Policy Optimization(C-SPPO)based on centralized decision process and considering policy entropy(S)is proposed.The proposed framework aims to plan the best scheduling scheme with the objective of minimizing both the timeout of order requests and the flight impact of UAVs that may lead to conflicts.In this framework,the intents of matching act are generated through the observations of UAV agents,and the ultimate conflict-free matching results are output under the guidance of a centralized decision maker.Concurrently,a pre-activation operation is introduced to further enhance the cooperation among UAV agents.Simulation experiments based on real-world data from New York City are conducted.The results indicate that the proposed CSPPO outperforms the baseline algorithms in the Average Delay Time(ADT),the Maximum Delay Time(MDT),the Order Delay Rate(ODR),the Average Flight Distance(AFD),and the Flight Impact Ratio(FIR).Furthermore,the framework demonstrates scalability to scenarios of different sizes without requiring additional training.
文摘As power systems expand,solving the unit commitment problem(UCP)becomes increasingly challenging due to the curse of dimensionality,and traditional methods often struggle to balance computational efficiency and solution optimality.To tackle this issue,we propose a problem-structure-informed quantum approximate optimization algorithm(QAOA)framework that fully exploits the quantum advantage under extremely limited quantum resources.Specifically,we leverage the inherent topological structure of power systems to decompose large-scale UCP instances into smaller subproblems,which are solvable in parallel by limited number of qubits.This decomposition not only circumvents the current hardware limitations of quantum computing but also achieves higher performance as the graph structure of the power system becomes more sparse.Consequently,our approach can be extended to future power systems that are larger and more complex.
基金funded by the National Natural Science Foundation of China(No.72104069)the Science and Technology Department of Henan Province,China(No.182102310886 and 162102110109)the Postgraduate Meritocracy Scheme,hina(No.SYL19060145).
文摘To solve large-scale optimization problems,Fragrance coefficient and variant Particle Swarm local search Butterfly Optimization Algorithm(FPSBOA)is proposed.In the position update stage of Butterfly Optimization Algorithm(BOA),the fragrance coefficient is designed to balance the exploration and exploitation of BOA.The variant particle swarm local search strategy is proposed to improve the local search ability of the current optimal butterfly and prevent the algorithm from falling into local optimality.192000-dimensional functions and 201000-dimensional CEC 2010 large-scale functions are used to verify FPSBOA for complex large-scale optimization problems.The experimental results are statistically analyzed by Friedman test and Wilcoxon rank-sum test.All attained results demonstrated that FPSBOA can better solve more challenging scientific and industrial real-world problems with thousands of variables.Finally,four mechanical engineering problems and one ten-dimensional process synthesis and design problem are applied to FPSBOA,which shows FPSBOA has the feasibility and effectiveness in real-world application problems.
基金support by the Open Project of Xiangjiang Laboratory(22XJ02003)the University Fundamental Research Fund(23-ZZCX-JDZ-28,ZK21-07)+5 种基金the National Science Fund for Outstanding Young Scholars(62122093)the National Natural Science Foundation of China(72071205)the Hunan Graduate Research Innovation Project(CX20230074)the Hunan Natural Science Foundation Regional Joint Project(2023JJ50490)the Science and Technology Project for Young and Middle-aged Talents of Hunan(2023TJZ03)the Science and Technology Innovation Program of Humnan Province(2023RC1002).
文摘Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.
基金the National Natural Science Foundation of China (6027401360474002)Shanghai Development Found for Science and Technology (04DZ11008).
文摘A modified bottleneck-based （MB） heuristic for large-scale job-shop scheduling problems with a welldefined bottleneck is suggested, which is simpler but more tailored than the shifting bottleneck （SB） procedure. In this algorithm, the bottleneck is first scheduled optimally while the non-bottleneck machines are subordinated around the solutions of the bottleneck schedule by some effective dispatching rules. Computational results indicate that the MB heuristic can achieve a better tradeoff between solution quality and computational time compared to SB procedure for medium-size problems. Furthermore, it can obtain a good solution in a short time for large-scale jobshop scheduling problems.
基金supported by the National Key Research and Development Program of China(2022YFE0206700)。
文摘1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.
基金supported by the National Key Research&Development Program of China(Grant No.2023YFC3008404)the Key Laboratory of Earth Fissures Geological Disaster,Ministry of Natural Resources,China(Grant Nos.EFGD20240609 and EFGD20240610).
文摘The recent upsurge in metro construction emphasizes the necessity of understanding the mechanical performance of metro shield tunnel subjected to the influence of ground fissures.In this study,a largescale experiment,in combination with numerical simulation,was conducted to investigate the influence of ground fissures on a metro shield tunnel.The results indicate that the lining contact pressure at the vault increases in the hanging wall while decreases in the footwall,resulting in a two-dimensional stress state of vertical shear and axial tension-compression,and simultaneous vertical dislocation and axial tilt for the segments around the ground fissure.In addition,the damage to curved bolts includes tensile yield,flexural yield,and shear twist,leading to obvious concrete lining damage,particularly at the vault,arch bottom,and hance,indicating that the joints in these positions are weak areas.The shield tunnel orthogonal to the ground fissure ultimately experiences shear failure,suggesting that the maximum actual dislocation of ground fissure that the structure can withstand is approximately 20 cm,and five segment rings in the hanging wall and six segment rings in the footwall also need to be reinforced.This study could provide a reference for metro design in ground fissure sites.
基金Supported by the National Key R&D Program of China(2024YFE0114000)Science and Technology Project of China National Petroleum Corporation(2024DJ8702).
文摘Based on the analysis of typical lacustrine shale oil zones in China and their geological characteristics,this study elucidates the fundamental differences between the enrichment patterns of shale oil sweet spots and conventional oil and gas.The key parameters and evaluation methods for assessing the large-scale production potential of lacustrine shale oil are proposed.The results show that shale oil is a petroleum resource that exists in organic-rich shale formations,in other words,it is preserved in its source bed,following a different process of generation-accumulation-enrichment from conventional oil and gas.Thus,the concept of“reservoir”seems to be inapplicable to shale oil.In China,lacustrine shale oil is distributed widely,but the geological characteristics and sweet spots enrichment patterns of shale oil vary significantly in lacustrine basins where the water environment and the tectonic evolution and diagenetic transformation frameworks are distinct.The core of the evaluation of lacustrine shale oil is“sweet spot volume”.The key factors for evaluating the large-scale production of continental shale oil are the oil storage capacity,oil-bearing capacity and oil producing capacity.The key parameters for evaluating these capacities are total porosity,oil content,and free oil content,respectively.It is recommended to determine the total porosity of shale by combining helium porosity measurement with nuclear magnetic resonance(NMR)method,the oil content of key layers by using organic solvent extraction,NMR method and high pressure mercury intrusion methods,and the free oil content by using NMR fluid distribution secondary spectral stripping decomposition and logging.The research results contribute supplemental insights on continental shale oil deliverability in China,and provide a scientific basis for the rapid exploration and large-scale production of lacustrine shale oil.
基金Supported by the National Natural Science Foundation of China(No.29906010).
文摘The performance of analytical derivative and sparse matrix techniques applied to a traditional dense sequential quadratic programming (SQP) is studied, and the strategy utilizing those techniques is also presented.Computational results on two typical chemical optimization problems demonstrate significant enhancement in efficiency, which shows this strategy is promising and suitable for large-scale process optimization problems.
基金National Natural Science Foundation of China(52375378)National Key Laboratory of Metal Forming Technology and Heavy Equipment(S2308100.W12)Huxiang High-Level Talent Gathering Project of Hunan Province(2021RC5001)。
文摘The titanium alloy strut serves as a key load-bearing component of aircraft landing gear,typically manufactured via forging.The friction condition has important influence on material flow and cavity filling during the forging process.Using the previously optimized shape and initial position of preform,the influence of the friction condition(friction factor m=0.1–0.3)on material flow and cavity filling was studied by numerical method with a shear friction model.A novel filling index was defined to reflect material flow into left and right flashes and zoom in on friction-induced results.The results indicate that the workpiece moves rigidly to the right direction,with the displacement decreasing as m increases.When m<0.18,the underfilling defect will occur in the left side of strut forging,while overflow occurs in the right forging die cavity.By combining the filling index and analyses of material flow and filling status,a reasonable friction factor interval of m=0.21–0.24 can be determined.Within this interval,the cavity filling behavior demonstrates robustness,with friction fluctuations exerting minimal influence.
基金Supported by Daqing City Philosophy and Social Sciences Planning Research Project(DSGB 2025011)the Heilongjiang Province Education Science Planning Key Project(GJB1320229).
文摘Based on questionnaire surveys and field interviews conducted with various types of agricultural production organizations across five districts and four counties in Daqing City,this study combines relevant theoretical frameworks to systematically examine the evolution,performance,and influencing factors of governance mechanisms within these organizations.Using both quantitative and inductive analytical methods,the paper proposes innovative designs and supporting measures for improving governance mechanisms.The findings reveal that,amid large-scale farmland circulation,the governance mechanisms of agricultural production organizations in Daqing City are evolving from traditional to modern structures.However,challenges remain in areas such as decision-making efficiency,benefit distribution,and supervision mechanisms.In response,this study proposes innovative governance designs focusing on decision-making processes,profit-sharing mechanisms,and risk prevention.Corresponding policy recommendations are also provided to support the sustainable development of agricultural modernization in China.
文摘This article focuses on the management of large-scale machinery and equipment in highway construction,with the research objective of identifying issues at the management level and exploring more effective management measures.Through practical observation and logical analysis,this article elaborates on the management connotations of large-scale machinery and equipment in highway construction,affirming its management value from different perspectives.On this basis,it carefully analyzes the problems existing in the management of large-scale machinery and equipment,providing a detailed interpretation of issues such as the weak foundation of the equipment management system and the disconnection between equipment selection and configuration from reality.Combining the manifestations of related problems,this article proposes strategies such as strengthening the institutional foundation of equipment management,selecting and configuring equipment based on actual conditions,aiming to provide references for large-scale machinery and equipment management to relevant enterprises.
基金supported by the Fundamental Research Funds for the Central Universities(Grant Nos.lzujbky-2021-62 and lzujbky-2024-jdzx06)the National Natural Science Foundation of China(Grant No.12247101)+1 种基金the Natural Science Foundation of Gansu Province,China(Grant Nos.22JR5RA389 and 23JRRA1740)the‘111 Center’Fund(Grant No.B20063).
文摘It has been argued that the human brain,as an information-processing machine,operates near a phase transition point in a non-equilibrium state,where it violates detailed balance leading to entropy production.Thus,the assessment of irreversibility in brain networks can provide valuable insights into their non-equilibrium properties.In this study,we utilized an open-source whole-brain functional magnetic resonance imaging(fMRI)dataset from both resting and task states to evaluate the irreversibility of large-scale human brain networks.Our analysis revealed that the brain networks exhibited significant irreversibility,violating detailed balance,and generating entropy.Notably,both physical and cognitive tasks increased the extent of this violation compared to the resting state.Regardless of the state(rest or task),interactions between pairs of brain regions were the primary contributors to this irreversibility.Moreover,we observed that as global synchrony increased within brain networks,so did irreversibility.The first derivative of irreversibility with respect to synchronization peaked near the phase transition point,characterized by the moderate mean synchronization and maximized synchronization entropy of blood oxygenation level-dependent(BOLD)signals.These findings deepen our understanding of the non-equilibrium dynamics of large-scale brain networks,particularly in relation to their phase transition behaviors,and may have potential clinical applications for brain disorders.
基金supported by the National Nature Science Foundation of China National Outstanding Youth Science Fund Project(Grant No.52122109)the National Natural Science Foundation of China(Grants No.51861165102 and 52039005).
文摘Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by conducting large-scale(1:13)experiments to investigate the scour hole pattern and equilibrium scour depth around both slender and large monopiles under irregular waves.The experiments adopted KeuleganeCarpenter number(NKC)values from 1.01 to 8.89 and diffraction parameter(D/L,where D is the diameter of the monopile,and L is the wave length)values from 0.016 to 0.056.The results showed that changes in the maximum scour location and scour hole shape around a slender monopile were associated with NKC,with differences observed between irregular and regular waves.Improving the calculation of NKC enhanced the accuracy of existing scour formulae under irregular waves.The maximum scour locations around a large monopile were consistently found on both sides,regardless of NKC and D/L,but the scour hole topography was influenced by both parameters.Notably,the scour range around a large monopile was at least as large as the monopile diameter.
基金Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004)National Natural Science Foundation of China (42275041)Hainan Province Science and Technology Special Fund (SOLZSKY2025006)。
文摘In 2022, South China(SC) experienced record-breaking rainfall during its first rainy season, causing severe socioeconomic losses. This study examines the large-scale circulation anomalies responsible for this extreme event.Analysis reveals that the lower-tropospheric cyclonic anomaly over SC plays a crucial role. This cyclonic anomaly consists of extratropical northeasterly anomalies to the north of SC and tropical southwesterly anomalies to the south. Both components were particularly intense during the 2022 first rainy season, contributing to the heavy rainfall in SC. Moreover,the lower-tropospheric cyclonic anomaly is enhanced by its counterpart in the upper troposphere, which is associated with a wave train propagating from the North Atlantic to East Asia across the mid-high latitudes of the Eurasian continent.Further analysis indicates that the extratropical wave train correlates with sea surface temperature anomalies(SSTAs) in the North Atlantic. Additionally, the SSTAs over the North Indian Ocean also play a role in enhancing the tropical southwesterlies in the lower troposphere. This study highlights the combined influence of tropical and extratropical circulation anomalies, offering a comprehensive understanding of the record-breaking rainfall.
文摘This study employs deformation monitoring data acquired during the construction of the Haoji railway large-scale bridge to investigate the displacement behavior of the subgrades,catenary columns,and tracks.Emphasis is placed on data acquisition and processing methods using total stations and automated monitoring systems.Through a comprehensive analysis of lateral,longitudinal,and vertical displacement data from 26 subgrade monitoring points,catenary columns,and track sections,this research evaluates how construction activities influence railway structures.The results show that displacement variations in the subgrades,catenary columns,and tracks remained within the established alert thresholds,exhibiting stable deformation trends and indicating that any adverse environmental impact was effectively contained.Furthermore,this paper proposes an early warning mechanism based on an automated monitoring system,which can promptly detect abnormal deformations and initiate emergency response procedures,thereby ensuring the safe operation of the railway.The integration of big data analysis and deformation prediction models offers a practical foundation for future safety management in railway construction.
文摘The research on optimization methods for constellation launch deployment strategies focused on the consideration of mission interval time constraints at the launch site.Firstly,a dynamic modeling of the constellation deployment process was established,and the relationship between the deployment window and the phase difference of the orbit insertion point,as well as the cost of phase adjustment after orbit insertion,was derived.Then,the combination of the constellation deployment position sequence was treated as a parameter,together with the sequence of satellite deployment intervals,as optimization variables,simplifying a highdimensional search problem within a wide range of dates to a finite-dimensional integer programming problem.An improved genetic algorithm with local search on deployment dates was introduced to optimize the launch deployment strategy.With the new description of the optimization variables,the total number of elements in the solution space was reduced by N orders of magnitude.Numerical simulation confirms that the proposed optimization method accelerates the convergence speed from hours to minutes.
