In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single-or multi-objective functions when utilizing automatic calibration approaches.In most previous studies,...In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single-or multi-objective functions when utilizing automatic calibration approaches.In most previous studies, there is a general opinion that no single-objective function can represent all important characteristics of even one specific hydrological variable(e.g., streamflow).Thus hydrologists must turn to multi-objective calibration.In this study, we demonstrated that an optimized single-objective function can compromise multi-response modes(i.e., multi-objective functions) of the hydrograph, which is defined as summation of a power function of the absolute error between observed and simulated streamflow with the exponent of power function optimized for specific watersheds.The new objective function was applied to 196 model parameter estimation experiment(MOPEX) watersheds across the eastern United States using the semi-distributed Xinanjiang hydrological model.The optimized exponent value for each watershed was obtained by targeting four popular objective functions focusing on peak flows, low flows, water balance, and flashiness, respectively.Results showed that the optimized single-objective function can achieve a better hydrograph simulation compared to the traditional single-objective function Nash-Sutcliffe efficiency coefficient for most watersheds, and balance high flow part and low flow part of the hydrograph without substantial differences compared to multi-objective calibration.The proposed optimal single-objective function can be practically adopted in the hydrological modeling if the optimal exponent value could be determined a priori according to hydrological/climatic/landscape characteristics in a specific watershed.展开更多
Efficiency and accuracy have been challenging in the design optimisation process driven by building simulation. The literature review identified the limitations of previous studies, prompting this study to explore the...Efficiency and accuracy have been challenging in the design optimisation process driven by building simulation. The literature review identified the limitations of previous studies, prompting this study to explore the performance of single-objective versus multi-objective efficiency and accuracy on equivalent problems based on control variables and to consider more algorithmic options for a broader range of designs. This study constructed a comparative energy-related experiment whose results are in the same unit, either as a single-objective optimisation or split into two objectives. The project aims to reduce annual energy consumption and increase solar utilisation potential. Our approach focuses on the use of a surrogate modelling algorithm, Radial Basis Function Optimisation Algorithm(RBFOpt),with its multi-objective version RBFMOpt, to optimise the energy performance while quickly identifying new energy requirements for an iterative office building design logic, contrast to traditional genetic-algorithm-driven. In addition, the research also conducted a comparative study between RBFOpt and Covariance Matrix Adaptation Evolutionary Strategies(CMAES) in a single-objective comparison and between RBFMOpt and Nondominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ) in a multi-objective optimisation process. The comparison of these sets of Opt algorithms with evolutionary algorithms helps to provide data-driven evidence to support early design decisions.展开更多
It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled.They contain reusable resource that can be recycled and used to generate desired econom...It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled.They contain reusable resource that can be recycled and used to generate desired economic benefits.Therefore,performing their efficient disassembly is highly important in green manufacturing and sustainable economic development.Their typical examples are electronic appliances and electromechanical/mechanical products.This paper presents a survey on the state of the art of disassembly sequence planning.It can help new researchers or decision makers to search for the right solution for optimal disassembly planning.It reviews the disassembly theory and methods that are applied for the processing,repair,and maintenance of obsolete/discarded products.This paper discusses the recent progress of disassembly sequencing planning in four major aspects:product disassembly modeling methods,mathematical programming methods,artificial intelligence methods,and uncertainty handling.This survey should stimulate readers to be engaged in the research,development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.展开更多
Geothermal energy,a kind of clean and environmentally friendly energy source,is an important object of future natural resource development and utilization,among which,hot dry rock is one of the important deep geotherm...Geothermal energy,a kind of clean and environmentally friendly energy source,is an important object of future natural resource development and utilization,among which,hot dry rock is one of the important deep geothermal resources.In the current multi-objective optimization of heat extraction performance,reservoir production models are less considered and the effects of different optimization ideas are not compared comprehensively.To improve the heat extraction efficiency and prolong the exploitation life of geothermal reservoirs,this paper determines the appropriate operating parameters of geothermal system(injection temperature,injection rate,production pressure and injection-production well spacing)based on the coupled thermal-hydraulic-mechanical model of hot dry rock exploitation in the Gonghe area of Qinghai and three heat extraction optimization methods.In addition,the heat extraction performances of different schemes are comparatively evaluated.And the following research results are obtained.First,the sensitivity analysis of injection and production parameters shows that power generation and recovery factor are in a reverse relation with injection-production pressure difference,which is the direct reason for the adoption of multiobjective optimization.Second,the optimization scheme prepared on the basis of parametric study indicates that the shortest life of a geothermal reservoir is 10 years,the injection-production pressure difference is up to 67 MPa,there is a significant thermal breakthrough phenomenon and the reservoir safety faces challenges.Third,by virtue of multi-objective optimization and decision making integration,the optimal operation parameter combination of hot dry rock system is determined,the life of geothermal reservoirs can exceed 20 years and balanced optimization is achieved.In conclusion,the idea of multi-objective optimization is feasible and applicable to geothermal energy exploitation and this method provides a reference for the efficient geothermal energy development and utilization and is helpful to the realization of“double carbon”goal in China.展开更多
Project scheduling problem is mainly to determine the schedule of allocating resources in order to balance the total cost and the completion time. This paper chiefly uses chance theory to introduce project scheduling ...Project scheduling problem is mainly to determine the schedule of allocating resources in order to balance the total cost and the completion time. This paper chiefly uses chance theory to introduce project scheduling problem with uncertain variables. First, two types of single-objective programming models with uncertain variables as uncertain chance-constrained model and uncertain maximization chance-constrained model are established to meet different management requirements, then they are extended to multi-objective programming model with uncertain variables.展开更多
In response to practical application challenges in utilizing solar-powered unmanned aerial vehicle(UAV)for remote sensing,this study presents a three-dimensional path planning method tailored for urban-mountainous env...In response to practical application challenges in utilizing solar-powered unmanned aerial vehicle(UAV)for remote sensing,this study presents a three-dimensional path planning method tailored for urban-mountainous environment.Taking into account constraints related to the solar-powered UAV,terrain,and mission objectives,a multi-objective trajectory optimization model is transferred into a single-objective optimization problem with weight factors and multiconstraint and is developed with a focus on three key indicators:minimizing trajectory length,maximizing energy flow efficiency,and minimizing regional risk levels.Additionally,an enhanced sparrow search algorithm incorporating the Levy flight strategy(SSA-Levy)is introduced to address trajectory planning challenges in such complex environments.Through simulation,the proposed algorithm is compared with particle swarm optimization(PSO)and the regular sparrow search algorithm(SSA)across 17 standard test functions and a simplified simulation of urban-mountainous environments.The results of the simulation demonstrate the superior effectiveness of the designed improved SSA based on the Levy flight strategy for solving the established single-objective trajectory optimization model.展开更多
基金Under the auspices of National Key Research and Development Program of China(No.2016YFC0402701)National Natural Science Foundation of China(No.51825902)
文摘In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single-or multi-objective functions when utilizing automatic calibration approaches.In most previous studies, there is a general opinion that no single-objective function can represent all important characteristics of even one specific hydrological variable(e.g., streamflow).Thus hydrologists must turn to multi-objective calibration.In this study, we demonstrated that an optimized single-objective function can compromise multi-response modes(i.e., multi-objective functions) of the hydrograph, which is defined as summation of a power function of the absolute error between observed and simulated streamflow with the exponent of power function optimized for specific watersheds.The new objective function was applied to 196 model parameter estimation experiment(MOPEX) watersheds across the eastern United States using the semi-distributed Xinanjiang hydrological model.The optimized exponent value for each watershed was obtained by targeting four popular objective functions focusing on peak flows, low flows, water balance, and flashiness, respectively.Results showed that the optimized single-objective function can achieve a better hydrograph simulation compared to the traditional single-objective function Nash-Sutcliffe efficiency coefficient for most watersheds, and balance high flow part and low flow part of the hydrograph without substantial differences compared to multi-objective calibration.The proposed optimal single-objective function can be practically adopted in the hydrological modeling if the optimal exponent value could be determined a priori according to hydrological/climatic/landscape characteristics in a specific watershed.
基金National Natural Science Foundation of China(Grant Nos.51978144,51978147)。
文摘Efficiency and accuracy have been challenging in the design optimisation process driven by building simulation. The literature review identified the limitations of previous studies, prompting this study to explore the performance of single-objective versus multi-objective efficiency and accuracy on equivalent problems based on control variables and to consider more algorithmic options for a broader range of designs. This study constructed a comparative energy-related experiment whose results are in the same unit, either as a single-objective optimisation or split into two objectives. The project aims to reduce annual energy consumption and increase solar utilisation potential. Our approach focuses on the use of a surrogate modelling algorithm, Radial Basis Function Optimisation Algorithm(RBFOpt),with its multi-objective version RBFMOpt, to optimise the energy performance while quickly identifying new energy requirements for an iterative office building design logic, contrast to traditional genetic-algorithm-driven. In addition, the research also conducted a comparative study between RBFOpt and Covariance Matrix Adaptation Evolutionary Strategies(CMAES) in a single-objective comparison and between RBFMOpt and Nondominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ) in a multi-objective optimisation process. The comparison of these sets of Opt algorithms with evolutionary algorithms helps to provide data-driven evidence to support early design decisions.
基金the Research Foundation of China(L2019027)Liaoning Revitalization Talents Program(XLYC1907166)the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah(KEP-2-135-39)。
文摘It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled.They contain reusable resource that can be recycled and used to generate desired economic benefits.Therefore,performing their efficient disassembly is highly important in green manufacturing and sustainable economic development.Their typical examples are electronic appliances and electromechanical/mechanical products.This paper presents a survey on the state of the art of disassembly sequence planning.It can help new researchers or decision makers to search for the right solution for optimal disassembly planning.It reviews the disassembly theory and methods that are applied for the processing,repair,and maintenance of obsolete/discarded products.This paper discusses the recent progress of disassembly sequencing planning in four major aspects:product disassembly modeling methods,mathematical programming methods,artificial intelligence methods,and uncertainty handling.This survey should stimulate readers to be engaged in the research,development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.
基金National Natural Science Foundation of China(NSFC)“Theory and Technology of Complex Seam Network in High Temperature Rock for Storage”(No.52192621)National Key Research and Development Program(No.2018YFB1501804)+2 种基金Sichuan Science and Technology Program Project“Research on the Mechanism of Enhanced Heat Transfer between Geothermal Well Completion Structure and Downhole Heat Exchanger”(No.2021Ya1.389)National Key Research and Development Program(No.2021YJ0389)“Research on the Mechanism of Fracture Damage in Dry Hot Rock Extraction”(PRP/open-2110)of the State Key Laboratory of Oil and Gas Resources and Exploration,China University of Petroleum(Beijing).
文摘Geothermal energy,a kind of clean and environmentally friendly energy source,is an important object of future natural resource development and utilization,among which,hot dry rock is one of the important deep geothermal resources.In the current multi-objective optimization of heat extraction performance,reservoir production models are less considered and the effects of different optimization ideas are not compared comprehensively.To improve the heat extraction efficiency and prolong the exploitation life of geothermal reservoirs,this paper determines the appropriate operating parameters of geothermal system(injection temperature,injection rate,production pressure and injection-production well spacing)based on the coupled thermal-hydraulic-mechanical model of hot dry rock exploitation in the Gonghe area of Qinghai and three heat extraction optimization methods.In addition,the heat extraction performances of different schemes are comparatively evaluated.And the following research results are obtained.First,the sensitivity analysis of injection and production parameters shows that power generation and recovery factor are in a reverse relation with injection-production pressure difference,which is the direct reason for the adoption of multiobjective optimization.Second,the optimization scheme prepared on the basis of parametric study indicates that the shortest life of a geothermal reservoir is 10 years,the injection-production pressure difference is up to 67 MPa,there is a significant thermal breakthrough phenomenon and the reservoir safety faces challenges.Third,by virtue of multi-objective optimization and decision making integration,the optimal operation parameter combination of hot dry rock system is determined,the life of geothermal reservoirs can exceed 20 years and balanced optimization is achieved.In conclusion,the idea of multi-objective optimization is feasible and applicable to geothermal energy exploitation and this method provides a reference for the efficient geothermal energy development and utilization and is helpful to the realization of“double carbon”goal in China.
文摘Project scheduling problem is mainly to determine the schedule of allocating resources in order to balance the total cost and the completion time. This paper chiefly uses chance theory to introduce project scheduling problem with uncertain variables. First, two types of single-objective programming models with uncertain variables as uncertain chance-constrained model and uncertain maximization chance-constrained model are established to meet different management requirements, then they are extended to multi-objective programming model with uncertain variables.
基金supported in part by the National Natural Science Foundation of China under Grant 51979275the National Key Research and Development Program of China under Grant 2022YFD2001405+8 种基金the open fund of Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province under Grant 2023ZJZD2306the Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities,Ministry of Natural Resources,under Grant KFKT-2022-05in part by Shenzhen Science and Technology Program(grant number ZDSYS20210623091808026)the Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems,Beihang University,under Grant VRLAB2022C10in part by the open fund project of State Key Laboratory of Clean Energy Utilization under Grant ZJUCEU2022002the open fund of Key Laboratory of Smart Agricultural Technology(Yangtze River Delta),Ministry of Agriculture and Rural Affairs,under Grant KSAT-YRD2023005the Open Project Program of Key Laboratory of Smart Agricultural Technology in Tropical South China,Ministry of Agriculture and Rural Affairs,under Grant HNZHNYKFKT-202202the Higher Education Scientific Research Planning Project,China Association of Higher Education,under Grant 23XXK0304the 2115 Talent Development Program of China Agricultural University.Ben Ma received the master's degree in mechatronics engineering at the College of Engineering,China Agricultural University,Beijing,China,in 2021.
文摘In response to practical application challenges in utilizing solar-powered unmanned aerial vehicle(UAV)for remote sensing,this study presents a three-dimensional path planning method tailored for urban-mountainous environment.Taking into account constraints related to the solar-powered UAV,terrain,and mission objectives,a multi-objective trajectory optimization model is transferred into a single-objective optimization problem with weight factors and multiconstraint and is developed with a focus on three key indicators:minimizing trajectory length,maximizing energy flow efficiency,and minimizing regional risk levels.Additionally,an enhanced sparrow search algorithm incorporating the Levy flight strategy(SSA-Levy)is introduced to address trajectory planning challenges in such complex environments.Through simulation,the proposed algorithm is compared with particle swarm optimization(PSO)and the regular sparrow search algorithm(SSA)across 17 standard test functions and a simplified simulation of urban-mountainous environments.The results of the simulation demonstrate the superior effectiveness of the designed improved SSA based on the Levy flight strategy for solving the established single-objective trajectory optimization model.
