Dear Editor,This letter investigates predefined-time optimization problems(OPs) of multi-agent systems(MASs), where the agent of MASs is subject to inequality constraints, and the team objective function accounts for ...Dear Editor,This letter investigates predefined-time optimization problems(OPs) of multi-agent systems(MASs), where the agent of MASs is subject to inequality constraints, and the team objective function accounts for impulse effects. Firstly, to address the inequality constraints,the penalty method is introduced. Then, a novel optimization strategy is developed, which only requires that the team objective function be strongly convex.展开更多
The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To th...The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To this end,this paper investigates the multi-timescale rolling opti-mization problem for IES integrated with HESS.Firstly,the architecture of IES with HESS is established,a comparative analysis is conducted to evaluate the advantages of the HESS over a single energy storage system(SESS)in stabilizing power fluctuations.Secondly,the dayahead and real-time scheduling cost functions of IES are established,the day-ahead scheduling mainly depends on operation costs of the components in IES,the real-time optimal scheduling adopts the Lya-punov optimization method to schedule the battery and hydrogen energy storage in each time slot,so as to minimize the real-time average scheduling operation cost,and the problem of day-ahead and real-time scheduling error,which caused by the uncertainty of the energy storage is solved by online optimization.Finally,the proposed model is verified to reduce the scheduling operation cost and the dispatching error by performing an arithmetic example analysis of the IES in Shanghai,which provides a reference for the safe and stable operation of the IES.展开更多
The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on...The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.展开更多
Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours ...Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.展开更多
The machining precision of blades is critical to the service performance of aero engines.The Leading Edge(LE) of high-pressure compressor blades poses a challenge for precision machining due to its thin size, high deg...The machining precision of blades is critical to the service performance of aero engines.The Leading Edge(LE) of high-pressure compressor blades poses a challenge for precision machining due to its thin size, high degree of bending, and significant change of curvature. Aimed at optimizing the machining error, this paper presents a framework that integrates toolpath planning and process parameter regulation. Firstly, an Iterative Subdivision Algorithm(ISA) for clamped Bspline curve is proposed, based on which toolpath planning method towards the LE is developed.Secondly, the removal effect of Cutter Contact(CC) point on the sampling points is investigated in the calculation of grinding dwell time by traversing in u-v space. A global material removal model is constructed for the solution. Thirdly, the previous two steps are interconnected based on the Improved Whale Optimization Algorithm(IWOA), and the optimal parameter combination is searched using the Root Mean Square Error(RMSE) of the machining error as the objective function. Based on this, the off-line programming and robotic grinding experiments are carried out. The experimental results show that the proposed method with error optimization can achieve 0.0143 mm mean value and 0.0160 mm standard deviations of LE surface error, which is an improvement of32.5% and 33.9%, respectively, compared with previous method.展开更多
In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants ...In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants in energy trading.Firstly,the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading.Secondly,the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant.Finally,a combination algorithm of improved robust optimization over time(ROOT)and CPLEX is proposed to solve the established game model.The experimental results indicate that under different fitness thresholds,the robust optimization results of the proposed algorithm are increased by 56.91%and 68.54%,respectively.The established bi-level game model effectively balances the benefits of different energy trading entities.The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59%.展开更多
The design and development of solar dryers are crucial in regions with abundant solar energy,such as Bhopal,India,where seasonal variations significantly impact the efficiency of drying processes.The paper is focused ...The design and development of solar dryers are crucial in regions with abundant solar energy,such as Bhopal,India,where seasonal variations significantly impact the efficiency of drying processes.The paper is focused on employing a comprehensive mathematical model to predict the dryer’s performance in drying the materials such as banana slices.To enhance this model,Hyper Tuned Swarm Optimization with Gradient Tree(HT_SOGT)was utilized to accurately predict and determine the optimal size of the dryer dimensions considering various mathematical calculations for material drying.The predictive model considered the influence of seasonal fluctuations,ensuring an efficient drying process with an objective function to optimize the drying time of an average of 7 hrs throughout the year.Across all recorded ambient temperatures(ranging from 16.985○C to 31.4○C),the outlet temperature of the solar dryer is consistently higher,ranging from 39.085○C to 66.2○C.The results show that the optimized dryer design,based on HT_SOGT modelling,significantly improves drying efficiency of the materials across varying conditions,making it suitable for sustainable applications in agriculture and food processing industries in the Bhopal region.展开更多
GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieve...GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.展开更多
In this study,we comprehensively characterized and optimized a cryogenic pure CsI(pCsI)detector.We utilized a 2 cm×2 cm×2 cm cube crystal coupled with a HAMAMATSU R11065 photomultiplier tube,achieving a rema...In this study,we comprehensively characterized and optimized a cryogenic pure CsI(pCsI)detector.We utilized a 2 cm×2 cm×2 cm cube crystal coupled with a HAMAMATSU R11065 photomultiplier tube,achieving a remarkable light yield of 35.2 PE/ke V_(ee)and an unprecedented energy resolution of 6.9%at 59.54 ke V.Additionally,we measured the scintillation decay time of pCsI,which was significantly shorter than that of CsI(Na)at room temperature.Furthermore,we investigated the impact of temperature,surface treatment and crystal shape on light yield.Notably,the light yield peaked at approximately 20 K and remained stable within the range of 70–100 K.The light yield of the polished crystals was approximately 1.5 times greater than that of the ground crystals,whereas the crystal shape exhibited minimal influence on the light yield.These results are crucial for the design of the 10 kg pCsI detector for the future CLOVERS(coherent elastic neutrino(V)-nucleus scattering at China Spallation Neutron Source(CSNS))experiment.展开更多
This paper presents an innovative and effective control strategy tailored for a deregulated,diversified energy system involving multiple interconnected area.Each area integrates a unique mix of power generation techno...This paper presents an innovative and effective control strategy tailored for a deregulated,diversified energy system involving multiple interconnected area.Each area integrates a unique mix of power generation technologies:Area 1 combines thermal,hydro,and distributed generation;Area 2 utilizes a blend of thermal units,distributed solar technologies(DST),and hydro power;andThird control area hosts geothermal power station alongside thermal power generation unit and hydropower units.The suggested control system employs a multi-layered approach,featuring a blended methodology utilizing the Tilted Integral Derivative controller(TID)and the Fractional-Order Integral method to enhance performance and stability.The parameters of this hybrid TID-FOI controller are finely tuned using an advanced optimization method known as the Walrus Optimization Algorithm(WaOA).Performance analysis reveals that the combined TID-FOI controller significantly outperforms the TID and PID controllers when comparing their dynamic response across various system configurations.The study also incorporates investigation of redox flow batteries within the broader scope of energy storage applications to assess their impact on system performance.In addition,the research explores the controller’s effectiveness under different power exchange scenarios in a deregulated market,accounting for restrictions on generation ramp rates and governor hysteresis effects in dynamic control.To ensure the reliability and resilience of the presented methodology,the system transitions and develops across a broad range of varying parameters and stochastic load fluctuation.To wrap up,the study offers a pioneering control approach-a hybrid TID-FOI controller optimized via the Walrus Optimization Algorithm(WaOA)-designed for enhanced stability and performance in a complex,three-region hybrid energy system functioning within a deregulated framework.展开更多
Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a ...Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.展开更多
Manned multi-rotor electric Vertical Takeoff and Landing(eVTOL)aircraft is prone to actuator saturation due to its weak yaw control efficiency.To address this inherent problem,a rotor cross-tilt configuration is appli...Manned multi-rotor electric Vertical Takeoff and Landing(eVTOL)aircraft is prone to actuator saturation due to its weak yaw control efficiency.To address this inherent problem,a rotor cross-tilt configuration is applied in this paper,with an optimization method proposed to improve the overall control efficiency of the vehicle.First,a flight dynamics model of a 500-kg manned multi-rotor eVTOL aircraft is established.The accuracy of the co-axial rotor model is verified using a single arm test bench,and the accuracy of the flight dynamics model is verified by the flight test data.Then,an optimization method is designed based on the flight dynamics model to calculate an optimal rotor cross-tilt mounting angle,which not only improves the yaw control efficiency,but also basically maintains the efficiency of other control channels.The ideal rotor cross-tilt mounting angle for the prototype is determined by comprehensively considering the optimal results with different payloads,forward flight speeds,and rotor mounting angle errors.Finally,the feasibility of the rotor cross-tilt mounting angle is proved by analyzing the control derivatives of the flight dynamics model,the test data of a ground three Degree-of-Freedom(3DOF)platform,and the actual flight data of the prototype.The results show that a fixed rotor cross-tilt mounting angle can achieve ideal yaw control effectiveness,improving yaw angle tracking and hold ability,increasing endurance time,and achieving good yaw control performance with different payloads and forward speeds.展开更多
Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been...Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.展开更多
Astrodynamical space test of relativity using optical devices optimized for gravitation wave detection （ASTROD- GW） is an optimization of ASTROD to focus on the goal of detection of gravitation waves. The detection ...Astrodynamical space test of relativity using optical devices optimized for gravitation wave detection （ASTROD- GW） is an optimization of ASTROD to focus on the goal of detection of gravitation waves. The detection sensitivity is shifted 52 times toward larger wavelength compared with that of laser interferometer space antenna （LISA）. The mission orbits of the three spacecrafts forming a nearly equilateral triangular array are chosen to be near the Sun–Earth Lagrange points L3, L4, and L5. The three spacecrafts range interferometrically with one another with an arm length of about 260 million kilometers. In order to attain the required sensitivity for ASTROD-GW, laser frequency noise must be suppressed to below the secondary noises such as the optical path noise, acceleration noise, etc. For suppressing laser frequency noise, we need to use time delay interferometry （TDI） to match the two different optical paths （times of travel）. Since planets and other solar-system bodies perturb the orbits of ASTROD-GW spacecraft and affect the TDI, we simulate the time delay numerically using CGC 2.7 （here, CGC stands for center for gravitation and cosmology） ephemeris framework. To conform to the ASTROD-GW planning, we work out a set of 20-year optimized mission orbits of ASTROD-GW spacecraft starting at June 21, 2028, and calculate the differences in optical path in the first and second generation TDIs separately for one-detector case. In our optimized mission orbits of 20 years, changes of arm lengths are less than 0.0003 AU; the relative Doppler velocities are all less than 3m/s. All the second generation TDI for one-detector case satisfies the ASTROD-GW requirement.展开更多
ASTROD-GW （ASTROD [astrodynamical space test of relativity using optical devices] optimized for gravitational wave detection） is a gravitational-wave mission with the aim of detecting gravitational waves from massiv...ASTROD-GW （ASTROD [astrodynamical space test of relativity using optical devices] optimized for gravitational wave detection） is a gravitational-wave mission with the aim of detecting gravitational waves from massive black holes, extreme mass ratio inspirais （EMRIs） and galactic compact binaries together with testing relativistic gravity and probing dark energy and cosmology. Mission orbits of the 3 spacecrafts forming a nearly equilateral triangular array are chosen to be near the Sun-Earth Lagrange points L3, L4, and L5. The 3 space, crafts range interferometrically with one another with arm length about 260 million kilometers. For 260 times longer arm length, the detection sensitivity of ASTROD- GW is 260 fold better than that of eLISA/NGO in the lower frequency region by assuming the same acceleration noise. Therefore, ASTROD-GW will be a better cosmological probe. In previous papers, we have worked out the time delay interferometry （TDI） for the ecliptic formation. To resolve the reflection ambiguity about the ecliptic plane in source position determination, we have changed the basic formation into slightly inclined formation with half-year precessionperiod. In this paper, we optimize a set of 10-year inclined ASTROD-GW mission orbits numerically using ephemeris framework starting at June 21, 2035, including cases of inclination angle with 0° （no inclination）, 0.5°, 1.0°, 1.5°, 2.0°, 2.5°, and 3.0°. We simulate the time delays of the first and second generation TDI configurations for the different inclinations, and compare/analyse the numerical results to attain the requisite sensitivity of ASTROD-GW by suppressing laser frequency noise below the secondary noises. To explicate our calculation process for different inclination cases, we take the 1.0° as an example to show the orbit optimization and TDI simulation.展开更多
AIM To optimize the hepatobiliary phase delay time(HBPDT) of Gd-EOB-DTPA-enhanced magnetic resonance imaging(GED-MRI) for more efficient identification of hepatocellular carcinoma(HCC) occurring in different degrees o...AIM To optimize the hepatobiliary phase delay time(HBPDT) of Gd-EOB-DTPA-enhanced magnetic resonance imaging(GED-MRI) for more efficient identification of hepatocellular carcinoma(HCC) occurring in different degrees of cirrhosis assessed by Child-Pugh(CP) score.METHODS The liver parenchyma signal intensity(LPSI), the liver parenchyma(LP)/HCC signal ratios, and the visibility of HCC at HBP-DT of 5, 10, 15, 20, and 25 min(i.e., DT-5, DT-10, DT-15, DT-20, and DT-25) after injection of GdEOB-DTPA were collected and analyzed in 73 patients with cirrhosis of different degrees of severity(including 42 patients suffering from HCC) and 18 healthy adult controls.RESULTS The LPSI increased with HBP-DT more significantly in the healthy group than in the cirrhosis group(F = 17.361, P < 0.001). The LP/HCC signal ratios had a significant difference(F = 12.453, P < 0.001) among various HBP-DT points, as well as between CP-A and CP-B/C subgroups(F = 9.761, P < 0.001). The constituent ratios of HCC foci identified as obvious hypointensity(+++), moderate hypointensity(++), and mild hypointensity or isointensity(+/-) kept stable from DT-10 to DT-25: 90.6%, 9.4%, and 0.0% in the CP-A subgroup; 50.0%, 50.0%, and 0.0% in the CP-B subgroup; and 0.0%, 0.0%, and 100.0% in the CP-C subgroup, respectively.CONCLUSION The severity of liver cirrhosis has significant negative influence on the HCC visualization by GED-MRI. DT-10 is more efficient and practical than other HBP-DT points to identify most of HCC foci emerging in CP-A cirrhosis, as well as in CP-B cirrhosis; but an HBP-DT of 15 min or longer seems more appropriate than DT-10 for visualization of HCC in patients with CP-C cirrhosis.展开更多
Based on the two-phase fluid （Eulerian-Eulerian） model, a mathematical model about the gas-liquid flow and mixing behavior was developed to investigate the effect of the offset of dual plugs, the included angle of d...Based on the two-phase fluid （Eulerian-Eulerian） model, a mathematical model about the gas-liquid flow and mixing behavior was developed to investigate the effect of the offset of dual plugs, the included angle of dual plugs with a center point, and gas flow rate on the mixing time in a ladle with dual plugs. Numerical results indicate that two types of recirculation zones exist in the ladle. One is the middle recirculation between gas and liquid plumes, and the other is the sidewall recirculation between plumes and the ladle sidewall. The correction shows that the mixing time is in proportion to -0.2676 power of gas flow rate. There is a unique optimum offset of dual plugs with a particular included angle, in turn, a unique optimum included angle of dual plugs exits with a particular offset.展开更多
Based on real time price counting of electric power, an optimization model of time sharing power for electrolytic zinc process(EZP) was established by means of an incremental fuzzy neural network(FNN), which is adopte...Based on real time price counting of electric power, an optimization model of time sharing power for electrolytic zinc process(EZP) was established by means of an incremental fuzzy neural network(FNN), which is adopted to approximate the relationship of current efficiency, current density and acidity. Penalty function introduced and optimal objective function reconstructed, a single loop simulated annealing algorithm(SAA) by using mutation and extending searching spaces was used to obtain optimal time sharing power scheme. Industrial practical results show that the whole system can greatly decrease the power consumption of EZP and increase the time sharing profits.展开更多
The observer-based robust fault detection filter design and optimization for networked control systems （NOSs） with uncer- tain time-varying delays are addressed. The NCSs with uncertain time-varying delays are model...The observer-based robust fault detection filter design and optimization for networked control systems （NOSs） with uncer- tain time-varying delays are addressed. The NCSs with uncertain time-varying delays are modeled as parameter-uncertain systems by the matrix theory. Based on the model, an observer-based residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of the linear matrix inequality. Furthermore, a time domain opti- mization approach is proposed to improve the performance of the fault detection system. To prevent the false alarms, a new thresh- old function is established, and the solution of the optimization problem is given by using the singular value decomposition （SVD） of the matrix. A numerical example is provided to illustrate the effectiveness of the proposed approach.展开更多
In the big data environment, enterprises must constantly assimilate big dataknowledge and private knowledge by multiple knowledge transfers to maintain theircompetitive advantage. The optimal time of knowledge transfe...In the big data environment, enterprises must constantly assimilate big dataknowledge and private knowledge by multiple knowledge transfers to maintain theircompetitive advantage. The optimal time of knowledge transfer is one of the mostimportant aspects to improve knowledge transfer efficiency. Based on the analysis of thecomplex characteristics of knowledge transfer in the big data environment, multipleknowledge transfers can be divided into two categories. One is the simultaneous transferof various types of knowledge, and the other one is multiple knowledge transfers atdifferent time points. Taking into consideration the influential factors, such as theknowledge type, knowledge structure, knowledge absorptive capacity, knowledge updaterate, discount rate, market share, profit contributions of each type of knowledge, transfercosts, product life cycle and so on, time optimization models of multiple knowledgetransfers in the big data environment are presented by maximizing the total discountedexpected profits (DEPs) of an enterprise. Some simulation experiments have beenperformed to verify the validity of the models, and the models can help enterprisesdetermine the optimal time of multiple knowledge transfer in the big data environment.展开更多
基金supported in part by the National Natural Science Foundation of China(62276119)the Natural Science Foundation of Jiangsu Province(BK20241764)the Postgraduate Research & Practice Innovation Program of Jiangsu Province(KYCX22_2860)
文摘Dear Editor,This letter investigates predefined-time optimization problems(OPs) of multi-agent systems(MASs), where the agent of MASs is subject to inequality constraints, and the team objective function accounts for impulse effects. Firstly, to address the inequality constraints,the penalty method is introduced. Then, a novel optimization strategy is developed, which only requires that the team objective function be strongly convex.
基金supported by the National Natural Science Foundation of China(No.12171145)。
文摘The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To this end,this paper investigates the multi-timescale rolling opti-mization problem for IES integrated with HESS.Firstly,the architecture of IES with HESS is established,a comparative analysis is conducted to evaluate the advantages of the HESS over a single energy storage system(SESS)in stabilizing power fluctuations.Secondly,the dayahead and real-time scheduling cost functions of IES are established,the day-ahead scheduling mainly depends on operation costs of the components in IES,the real-time optimal scheduling adopts the Lya-punov optimization method to schedule the battery and hydrogen energy storage in each time slot,so as to minimize the real-time average scheduling operation cost,and the problem of day-ahead and real-time scheduling error,which caused by the uncertainty of the energy storage is solved by online optimization.Finally,the proposed model is verified to reduce the scheduling operation cost and the dispatching error by performing an arithmetic example analysis of the IES in Shanghai,which provides a reference for the safe and stable operation of the IES.
基金supported by the National Natural Science Foundation of China(62176218,62176027)the Fundamental Research Funds for the Central Universities(XDJK2020TY003)the Funds for Chongqing Talent Plan(cstc2024ycjh-bgzxm0082)。
文摘The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.
基金Key R&D Program of Tianjin,China(No.20YFYSGX00060).
文摘Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.
基金supported by the National Natural Science Foundation of China (No. 52075059)Graduate Scientific Research and Innovation Foundation of Chongqing (No. CYB23021)the Innovation Fund of Aero Engine Corporation of China (No. ZZCX-2022-019)。
文摘The machining precision of blades is critical to the service performance of aero engines.The Leading Edge(LE) of high-pressure compressor blades poses a challenge for precision machining due to its thin size, high degree of bending, and significant change of curvature. Aimed at optimizing the machining error, this paper presents a framework that integrates toolpath planning and process parameter regulation. Firstly, an Iterative Subdivision Algorithm(ISA) for clamped Bspline curve is proposed, based on which toolpath planning method towards the LE is developed.Secondly, the removal effect of Cutter Contact(CC) point on the sampling points is investigated in the calculation of grinding dwell time by traversing in u-v space. A global material removal model is constructed for the solution. Thirdly, the previous two steps are interconnected based on the Improved Whale Optimization Algorithm(IWOA), and the optimal parameter combination is searched using the Root Mean Square Error(RMSE) of the machining error as the objective function. Based on this, the off-line programming and robotic grinding experiments are carried out. The experimental results show that the proposed method with error optimization can achieve 0.0143 mm mean value and 0.0160 mm standard deviations of LE surface error, which is an improvement of32.5% and 33.9%, respectively, compared with previous method.
基金supported by the National Nature Science Foundation of China(Nos.62063019)Natural Science Foundation of Gansu Province(22JR5RA241,2023CXZX-465).
文摘In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants in energy trading.Firstly,the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading.Secondly,the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant.Finally,a combination algorithm of improved robust optimization over time(ROOT)and CPLEX is proposed to solve the established game model.The experimental results indicate that under different fitness thresholds,the robust optimization results of the proposed algorithm are increased by 56.91%and 68.54%,respectively.The established bi-level game model effectively balances the benefits of different energy trading entities.The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59%.
文摘The design and development of solar dryers are crucial in regions with abundant solar energy,such as Bhopal,India,where seasonal variations significantly impact the efficiency of drying processes.The paper is focused on employing a comprehensive mathematical model to predict the dryer’s performance in drying the materials such as banana slices.To enhance this model,Hyper Tuned Swarm Optimization with Gradient Tree(HT_SOGT)was utilized to accurately predict and determine the optimal size of the dryer dimensions considering various mathematical calculations for material drying.The predictive model considered the influence of seasonal fluctuations,ensuring an efficient drying process with an objective function to optimize the drying time of an average of 7 hrs throughout the year.Across all recorded ambient temperatures(ranging from 16.985○C to 31.4○C),the outlet temperature of the solar dryer is consistently higher,ranging from 39.085○C to 66.2○C.The results show that the optimized dryer design,based on HT_SOGT modelling,significantly improves drying efficiency of the materials across varying conditions,making it suitable for sustainable applications in agriculture and food processing industries in the Bhopal region.
基金supported by the National Natural Science Foundation of China(Grant Nos.42404017,42122025 and 42174030).
文摘GNSS time series analysis provides an effective method for research on the earth's surface deformation,and it can be divided into two parts,deterministic models and stochastic models.The former part can be achieved by several parameters,such as polynomial terms,periodic terms,offsets,and post-seismic models.The latter contains some stochastic noises,which can be affected by detecting the former parameters.If there are not enough parameters assumed,modeling errors will occur and adversely affect the analysis results.In this study,we propose a processing strategy in which the commonly-used 1-order of the polynomial term can be replaced with different orders for better fitting GNSS time series of the Crustal Movement Network of China(CMONOC)stations.Initially,we use the Bayesian Information Criterion(BIC)to identify the best order within the range of 1-4 during the fitting process using the white noise plus power-law noise(WN+PL)model.Then,we compare the 1-order and the optimal order on the effect of deterministic models in GNSS time series,including the velocity and its uncertainty,amplitudes,and initial phases of the annual signals.The results indicate that the first-order polynomial in the GNSS time series is not the primary factor.The root mean square(RMS)reduction rates of almost all station components are positive,which means the new fitting of optimal-order polynomial helps to reduce the RMS of residual series.Most stations maintain the velocity difference(VD)within ±1 mm/yr,with percentages of 85.6%,81.9%and 63.4%in the North,East,and Up components,respectively.As for annual signals,the numbers of amplitude difference(AD)remained at ±0.2 mm are 242,239,and 200 in three components,accounting for 99.6%,98.4%,and 82.3%,respectively.This finding reminds us that the detection of the optimal-order polynomial is necessary when we aim to acquire an accurate understanding of the crustal movement features.
基金supported by the National Key R&D Program of China(No.2022YFA1602204)the National Natural Science Foundation of China(Nos.12175241,12221005)+2 种基金the Fundamental Research Funds for the Central Universitiesthe International Partnership Program of the Chinese Academy of Sciences(No.211134KYSB20200057)the Double First-Class University Project Foundation of USTC。
文摘In this study,we comprehensively characterized and optimized a cryogenic pure CsI(pCsI)detector.We utilized a 2 cm×2 cm×2 cm cube crystal coupled with a HAMAMATSU R11065 photomultiplier tube,achieving a remarkable light yield of 35.2 PE/ke V_(ee)and an unprecedented energy resolution of 6.9%at 59.54 ke V.Additionally,we measured the scintillation decay time of pCsI,which was significantly shorter than that of CsI(Na)at room temperature.Furthermore,we investigated the impact of temperature,surface treatment and crystal shape on light yield.Notably,the light yield peaked at approximately 20 K and remained stable within the range of 70–100 K.The light yield of the polished crystals was approximately 1.5 times greater than that of the ground crystals,whereas the crystal shape exhibited minimal influence on the light yield.These results are crucial for the design of the 10 kg pCsI detector for the future CLOVERS(coherent elastic neutrino(V)-nucleus scattering at China Spallation Neutron Source(CSNS))experiment.
文摘This paper presents an innovative and effective control strategy tailored for a deregulated,diversified energy system involving multiple interconnected area.Each area integrates a unique mix of power generation technologies:Area 1 combines thermal,hydro,and distributed generation;Area 2 utilizes a blend of thermal units,distributed solar technologies(DST),and hydro power;andThird control area hosts geothermal power station alongside thermal power generation unit and hydropower units.The suggested control system employs a multi-layered approach,featuring a blended methodology utilizing the Tilted Integral Derivative controller(TID)and the Fractional-Order Integral method to enhance performance and stability.The parameters of this hybrid TID-FOI controller are finely tuned using an advanced optimization method known as the Walrus Optimization Algorithm(WaOA).Performance analysis reveals that the combined TID-FOI controller significantly outperforms the TID and PID controllers when comparing their dynamic response across various system configurations.The study also incorporates investigation of redox flow batteries within the broader scope of energy storage applications to assess their impact on system performance.In addition,the research explores the controller’s effectiveness under different power exchange scenarios in a deregulated market,accounting for restrictions on generation ramp rates and governor hysteresis effects in dynamic control.To ensure the reliability and resilience of the presented methodology,the system transitions and develops across a broad range of varying parameters and stochastic load fluctuation.To wrap up,the study offers a pioneering control approach-a hybrid TID-FOI controller optimized via the Walrus Optimization Algorithm(WaOA)-designed for enhanced stability and performance in a complex,three-region hybrid energy system functioning within a deregulated framework.
基金The National Natural Science Foundation of China(No.61074147)the Natural Science Foundation of Guangdong Province(No.S2011010005059)+2 种基金the Foundation of Enterprise-University-Research Institute Cooperation from Guangdong Province and Ministry of Education of China(No.2012B091000171,2011B090400460)the Science and Technology Program of Guangdong Province(No.2012B050600028)the Science and Technology Program of Huadu District,Guangzhou(No.HD14ZD001)
文摘Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.
基金co-supported by the National Natural Science Foundation of China(Nos.12202406,11672128)。
文摘Manned multi-rotor electric Vertical Takeoff and Landing(eVTOL)aircraft is prone to actuator saturation due to its weak yaw control efficiency.To address this inherent problem,a rotor cross-tilt configuration is applied in this paper,with an optimization method proposed to improve the overall control efficiency of the vehicle.First,a flight dynamics model of a 500-kg manned multi-rotor eVTOL aircraft is established.The accuracy of the co-axial rotor model is verified using a single arm test bench,and the accuracy of the flight dynamics model is verified by the flight test data.Then,an optimization method is designed based on the flight dynamics model to calculate an optimal rotor cross-tilt mounting angle,which not only improves the yaw control efficiency,but also basically maintains the efficiency of other control channels.The ideal rotor cross-tilt mounting angle for the prototype is determined by comprehensively considering the optimal results with different payloads,forward flight speeds,and rotor mounting angle errors.Finally,the feasibility of the rotor cross-tilt mounting angle is proved by analyzing the control derivatives of the flight dynamics model,the test data of a ground three Degree-of-Freedom(3DOF)platform,and the actual flight data of the prototype.The results show that a fixed rotor cross-tilt mounting angle can achieve ideal yaw control effectiveness,improving yaw angle tracking and hold ability,increasing endurance time,and achieving good yaw control performance with different payloads and forward speeds.
文摘Flexible job shop scheduling problem(FJSP)is the core decision-making problem of intelligent manufacturing production management.The Harris hawk optimization(HHO)algorithm,as a typical metaheuristic algorithm,has been widely employed to solve scheduling problems.However,HHO suffers from premature convergence when solving NP-hard problems.Therefore,this paper proposes an improved HHO algorithm(GNHHO)to solve the FJSP.GNHHO introduces an elitism strategy,a chaotic mechanism,a nonlinear escaping energy update strategy,and a Gaussian random walk strategy to prevent premature convergence.A flexible job shop scheduling model is constructed,and the static and dynamic FJSP is investigated to minimize the makespan.This paper chooses a two-segment encoding mode based on the job and the machine of the FJSP.To verify the effectiveness of GNHHO,this study tests it in 23 benchmark functions,10 standard job shop scheduling problems(JSPs),and 5 standard FJSPs.Besides,this study collects data from an agricultural company and uses the GNHHO algorithm to optimize the company’s FJSP.The optimized scheduling scheme demonstrates significant improvements in makespan,with an advancement of 28.16%for static scheduling and 35.63%for dynamic scheduling.Moreover,it achieves an average increase of 21.50%in the on-time order delivery rate.The results demonstrate that the performance of the GNHHO algorithm in solving FJSP is superior to some existing algorithms.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 10778710 and 10875171)
文摘Astrodynamical space test of relativity using optical devices optimized for gravitation wave detection （ASTROD- GW） is an optimization of ASTROD to focus on the goal of detection of gravitation waves. The detection sensitivity is shifted 52 times toward larger wavelength compared with that of laser interferometer space antenna （LISA）. The mission orbits of the three spacecrafts forming a nearly equilateral triangular array are chosen to be near the Sun–Earth Lagrange points L3, L4, and L5. The three spacecrafts range interferometrically with one another with an arm length of about 260 million kilometers. In order to attain the required sensitivity for ASTROD-GW, laser frequency noise must be suppressed to below the secondary noises such as the optical path noise, acceleration noise, etc. For suppressing laser frequency noise, we need to use time delay interferometry （TDI） to match the two different optical paths （times of travel）. Since planets and other solar-system bodies perturb the orbits of ASTROD-GW spacecraft and affect the TDI, we simulate the time delay numerically using CGC 2.7 （here, CGC stands for center for gravitation and cosmology） ephemeris framework. To conform to the ASTROD-GW planning, we work out a set of 20-year optimized mission orbits of ASTROD-GW spacecraft starting at June 21, 2028, and calculate the differences in optical path in the first and second generation TDIs separately for one-detector case. In our optimized mission orbits of 20 years, changes of arm lengths are less than 0.0003 AU; the relative Doppler velocities are all less than 3m/s. All the second generation TDI for one-detector case satisfies the ASTROD-GW requirement.
文摘ASTROD-GW （ASTROD [astrodynamical space test of relativity using optical devices] optimized for gravitational wave detection） is a gravitational-wave mission with the aim of detecting gravitational waves from massive black holes, extreme mass ratio inspirais （EMRIs） and galactic compact binaries together with testing relativistic gravity and probing dark energy and cosmology. Mission orbits of the 3 spacecrafts forming a nearly equilateral triangular array are chosen to be near the Sun-Earth Lagrange points L3, L4, and L5. The 3 space, crafts range interferometrically with one another with arm length about 260 million kilometers. For 260 times longer arm length, the detection sensitivity of ASTROD- GW is 260 fold better than that of eLISA/NGO in the lower frequency region by assuming the same acceleration noise. Therefore, ASTROD-GW will be a better cosmological probe. In previous papers, we have worked out the time delay interferometry （TDI） for the ecliptic formation. To resolve the reflection ambiguity about the ecliptic plane in source position determination, we have changed the basic formation into slightly inclined formation with half-year precessionperiod. In this paper, we optimize a set of 10-year inclined ASTROD-GW mission orbits numerically using ephemeris framework starting at June 21, 2035, including cases of inclination angle with 0° （no inclination）, 0.5°, 1.0°, 1.5°, 2.0°, 2.5°, and 3.0°. We simulate the time delays of the first and second generation TDI configurations for the different inclinations, and compare/analyse the numerical results to attain the requisite sensitivity of ASTROD-GW by suppressing laser frequency noise below the secondary noises. To explicate our calculation process for different inclination cases, we take the 1.0° as an example to show the orbit optimization and TDI simulation.
文摘AIM To optimize the hepatobiliary phase delay time(HBPDT) of Gd-EOB-DTPA-enhanced magnetic resonance imaging(GED-MRI) for more efficient identification of hepatocellular carcinoma(HCC) occurring in different degrees of cirrhosis assessed by Child-Pugh(CP) score.METHODS The liver parenchyma signal intensity(LPSI), the liver parenchyma(LP)/HCC signal ratios, and the visibility of HCC at HBP-DT of 5, 10, 15, 20, and 25 min(i.e., DT-5, DT-10, DT-15, DT-20, and DT-25) after injection of GdEOB-DTPA were collected and analyzed in 73 patients with cirrhosis of different degrees of severity(including 42 patients suffering from HCC) and 18 healthy adult controls.RESULTS The LPSI increased with HBP-DT more significantly in the healthy group than in the cirrhosis group(F = 17.361, P < 0.001). The LP/HCC signal ratios had a significant difference(F = 12.453, P < 0.001) among various HBP-DT points, as well as between CP-A and CP-B/C subgroups(F = 9.761, P < 0.001). The constituent ratios of HCC foci identified as obvious hypointensity(+++), moderate hypointensity(++), and mild hypointensity or isointensity(+/-) kept stable from DT-10 to DT-25: 90.6%, 9.4%, and 0.0% in the CP-A subgroup; 50.0%, 50.0%, and 0.0% in the CP-B subgroup; and 0.0%, 0.0%, and 100.0% in the CP-C subgroup, respectively.CONCLUSION The severity of liver cirrhosis has significant negative influence on the HCC visualization by GED-MRI. DT-10 is more efficient and practical than other HBP-DT points to identify most of HCC foci emerging in CP-A cirrhosis, as well as in CP-B cirrhosis; but an HBP-DT of 15 min or longer seems more appropriate than DT-10 for visualization of HCC in patients with CP-C cirrhosis.
基金supported by the National High-tech Research and Development Program of China (No.2009AA03Z530)the National Natural Science Foundation of China and Shanghai Baosteel (No.50834010)the Key Project of the Ministry of Education of China (No.108036)
文摘Based on the two-phase fluid （Eulerian-Eulerian） model, a mathematical model about the gas-liquid flow and mixing behavior was developed to investigate the effect of the offset of dual plugs, the included angle of dual plugs with a center point, and gas flow rate on the mixing time in a ladle with dual plugs. Numerical results indicate that two types of recirculation zones exist in the ladle. One is the middle recirculation between gas and liquid plumes, and the other is the sidewall recirculation between plumes and the ladle sidewall. The correction shows that the mixing time is in proportion to -0.2676 power of gas flow rate. There is a unique optimum offset of dual plugs with a particular included angle, in turn, a unique optimum included angle of dual plugs exits with a particular offset.
文摘Based on real time price counting of electric power, an optimization model of time sharing power for electrolytic zinc process(EZP) was established by means of an incremental fuzzy neural network(FNN), which is adopted to approximate the relationship of current efficiency, current density and acidity. Penalty function introduced and optimal objective function reconstructed, a single loop simulated annealing algorithm(SAA) by using mutation and extending searching spaces was used to obtain optimal time sharing power scheme. Industrial practical results show that the whole system can greatly decrease the power consumption of EZP and increase the time sharing profits.
基金supported by the National Natural Science Foundation of China(6107402761273083)
文摘The observer-based robust fault detection filter design and optimization for networked control systems （NOSs） with uncer- tain time-varying delays are addressed. The NCSs with uncertain time-varying delays are modeled as parameter-uncertain systems by the matrix theory. Based on the model, an observer-based residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of the linear matrix inequality. Furthermore, a time domain opti- mization approach is proposed to improve the performance of the fault detection system. To prevent the false alarms, a new thresh- old function is established, and the solution of the optimization problem is given by using the singular value decomposition （SVD） of the matrix. A numerical example is provided to illustrate the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation ofChina (Grant No. 71704016,71331008, 71402010)the Natural Science Foundation of HunanProvince (Grant No. 2017JJ2267)+1 种基金the Educational Economy and Financial Research Base ofHunan Province (Grant No. 13JCJA2)the Project of China Scholarship Council forOverseas Studies (201508430121, 201208430233).
文摘In the big data environment, enterprises must constantly assimilate big dataknowledge and private knowledge by multiple knowledge transfers to maintain theircompetitive advantage. The optimal time of knowledge transfer is one of the mostimportant aspects to improve knowledge transfer efficiency. Based on the analysis of thecomplex characteristics of knowledge transfer in the big data environment, multipleknowledge transfers can be divided into two categories. One is the simultaneous transferof various types of knowledge, and the other one is multiple knowledge transfers atdifferent time points. Taking into consideration the influential factors, such as theknowledge type, knowledge structure, knowledge absorptive capacity, knowledge updaterate, discount rate, market share, profit contributions of each type of knowledge, transfercosts, product life cycle and so on, time optimization models of multiple knowledgetransfers in the big data environment are presented by maximizing the total discountedexpected profits (DEPs) of an enterprise. Some simulation experiments have beenperformed to verify the validity of the models, and the models can help enterprisesdetermine the optimal time of multiple knowledge transfer in the big data environment.
