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A Robust Damage Identification Method Based on Modified Holistic Swarm Optimization Algorithm and Hybrid Objective Function 认领 引用
1
作者 Xiansong Xie Xiaoqian Qian 《Structural Durability & Health Monitoring》 EI 2026年第2期235-259,共25页
Correlation function of acceleration responses-based damage identificationmethods has been developed and employed,while they still face the difficulty in identifying local orminor structural damages.To deal with this ... Correlation function of acceleration responses-based damage identificationmethods has been developed and employed,while they still face the difficulty in identifying local orminor structural damages.To deal with this issue,a robust structural damage identification method is developed,integrating a modified holistic swarm optimization(MHSO)algorithm with a hybrid objective function.The MHSO is developed by combining Hammersley sequencebased population initialization,chaotic search around the worst solution,and Hooke-Jeeves pattern search around the best solution,thereby improving both global exploration and local exploitation capabilities.A hybrid objective function is constructed by merging acceleration correlation function-based and strain correlation function-based objective functions,effectively leveraging the complementary sensitivities of global and local responses.To further suppress spurious solutions and promote sparsity in parameter estimation,an additional L0.5 regularization term is introduced.The effectiveness of the proposed method is validated through numerical simulations on a simply supported beam and a steel girder benchmark structure.Comparative studies with sequential quadratic programming,genetic algorithm,andHSO demonstrate that theMHSOachieves superior accuracy and convergence efficiency,even with limited sensors and 20%noise-contaminated measurements.Results highlight that the hybrid objective function significantly enhances the detection of both major and minor damages,while the inclusion of sparse regularization improves robustness against noise and model uncertainties.The findings indicate that the proposed framework provides a reliable and computationally efficient solution for simultaneous localization and quantification of structural damages,offering promising applicability to real-world structural health monitoring scenarios. 展开更多
关键词 Damage identification holistic swarm optimization algorithm combined correlation function hybrid objective function sparse regularization grid structure
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Predefined-Time Distributed Optimization for Resource Allocation Problems With Time-Varying Objective Function and Constraints 认领 引用
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作者 Haotian Wu Yang Liu +1 位作者 Mahmoud Abdel-Aty Weihua Gui 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第11期2353-2355,共3页
Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,... Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,a distributed control protocol is proposed for optimal resource allocation.The convergence to a time-varying optimal solution within a predefined time is proved.Two numerical examples are given to illustrate the effectiveness of the proposed approach. 展开更多
关键词 resource allocation distributed optimization time varying objective function optimal resource allocationthe distributed control protocol time varying constraints predefined time convergence
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A Novel Reliable and Trust Objective Function for RPL-Based IoT Routing Protocol 认领 引用
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作者 Mariam A.Alotaibi Sami S.Alwakeel Aasem N.Alyahya 《Computers, Materials & Continua》 SCIE EI 2025年第2期3467-3497,共31页
The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the... The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the selection of appropriate routing protocols, which is crucial for maintaining high Quality of Service (QoS). The Internet Engineering Task Force’s Routing Over Low Power and Lossy Networks (IETF ROLL) working group developed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) to meet these needs. While the initial RPL standard focused on single-metric route selection, ongoing research explores enhancing RPL by incorporating multiple routing metrics and developing new Objective Functions (OFs). This paper introduces a novel Objective Function (OF), the Reliable and Secure Objective Function (RSOF), designed to enhance the reliability and trustworthiness of parent selection at both the node and link levels within IoT and RPL routing protocols. The RSOF employs an adaptive parent node selection mechanism that incorporates multiple metrics, including Residual Energy (RE), Expected Transmission Count (ETX), Extended RPL Node Trustworthiness (ERNT), and a novel metric that measures node failure rate (NFR). In this mechanism, nodes with a high NFR are excluded from the parent selection process to improve network reliability and stability. The proposed RSOF was evaluated using random and grid topologies in the Cooja Simulator, with tests conducted across small, medium, and large-scale networks to examine the impact of varying node densities. The simulation results indicate a significant improvement in network performance, particularly in terms of average latency, packet acknowledgment ratio (PAR), packet delivery ratio (PDR), and Control Message Overhead (CMO), compared to the standard Minimum Rank with Hysteresis Objective Function (MRHOF). 展开更多
关键词 IoT LLNs RPL objective function OF MRHOF OF0 routing metrics reliability trustworthiness
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Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm 认领 引用 被引量：10
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作者 Qi-Hong Feng Shan-Shan Li +2 位作者 Xian-Min Zhang Xiao-Fei Gao Ji-Hui Ni 《Petroleum Science》 SCIE CAS CSCD 2022年第6期2879-2894,共16页
Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.T... Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency.To improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is established.This new objective function,which represents the water flooding potential,is extracted from streamline features.It only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the simulator.Then the well production optimization model is established and solved by the BADS algorithm.The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples.Results demonstrate that the new objective function is positively correlated with the cumulative oil production.And the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization accuracy.Besides,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods.It can provide a more effective basis for determining the optimal well production for actual oilfield development. 展开更多
关键词 Well production Optimization efficiency Streamline simulation Streamline feature Objective function Bayesian adaptive direct search algorithm
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Reactor Network Synthesis Based on Instantaneous Objective Function Characteristic Curves 认领 引用 被引量：2
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作者 张治山 赵文 +2 位作者 王艳丽 周传光 袁希钢 《Chinese Journal of Chemical Engineering》 SCIE EI CAS 2003年第4期436-440,共5页
It is believed that whether the instantaneous objective function curves of plug-flow-reactor (PFR) and continuous-stirred-tank-reactor (CSTR) overlap or not, they have a consistent changing trend for complex reactions... It is believed that whether the instantaneous objective function curves of plug-flow-reactor (PFR) and continuous-stirred-tank-reactor (CSTR) overlap or not, they have a consistent changing trend for complex reactions (steady state, isothermal and constant volume). As a result of the relation of the objective functions (selectivity or yield) to the instantaneous objective functions (instantaneous selectivity or instantaneous reaction rate), the optimal reactor network configuration can be determined according to the changing trend of the instantaneous objective function curves. Further, a recent partition strategy for the reactor network synthesis based on the instantaneous objective function characteristic curves is proposed by extending the attainable region partition strategy from the concentration space to the instantaneous objective function-unreacted fraction of key reactant space. In this paper, the instantaneous objective function is closed to be the instantaneous selectivity and several samples are examined to illustrate the proposed method. The comparison with the previous work indicates it is a very convenient and practical systematic tool of the reactor network synthesis and seems also promising for overcoming the dimension limit of the attainable region partition strategy in the concentration space. 展开更多
关键词 reactor network synthesis instantaneous objective function partition
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SELECTION OF OBJECTIVE FUNCTIONS AND APPLICATION OF GENETIC ALGORITHMS IN DAMPING DESIGN OF PIPE SYSTEM 认领 引用 被引量：1
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作者 ChenYanqiu FanQinsban ZhuZigen 《Acta Mechanica Solida Sinica》 SCIE 2003年第2期171-178,共8页
The vibration failure of pipe system of aeroengine seriously influences the safety of aircraft.Its damping design is determined by the selection of the design target,method and their feasibility.Five objective functio... The vibration failure of pipe system of aeroengine seriously influences the safety of aircraft.Its damping design is determined by the selection of the design target,method and their feasibility.Five objective functions for the vibration design of a pipeline or pipe system are introduced,namely,the frequency,amplitude,transfer ratio,curvature and deformation energy as options for the optimization process.The genetic algorithms(GA)are adopted as the opti- mization method,in which the selection of the adaptive genetic operators and the method of implementation of the GA process are crucial.The optimization procedure for all the above ob- jective functions is carried out using GA on the basis of finite element software-MSC/NASTRAN. The optimal solutions of these functions and the stress distribution on the structure are calculated and compared through an example,and their characteristics are analyzed.Finally we put forward two new objective functions,curvature and deformation energy for pipe system optimization.The calculations show that using the curvature as the objective function can reflect the case of minimal stress,and the optimization results using the deformation energy represent lesser and more uni- form stress distribution.The calculation results and process showed that the genetic algorithms can effectively implement damping design of engine pipelines and satisfy the efficient engineering design requirement. 展开更多
关键词 objective function genetic algorithms optimization pipe system
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OPTIMALITY CONDITIONS AND DUALITY RESULTS FOR NONSMOOTH VECTOR OPTIMIZATION PROBLEMS WITH THE MULTIPLE INTERVAL-VALUED OBJECTIVE FUNCTION 认领 引用 被引量：6
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作者 Tadeusz ANTCZAK 《Acta Mathematica Scientia》 SCIE CSCD 2017年第4期1133-1150,共18页
In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a （weakly） LU-efficient solution in the considered nonsmooth multiobjective programming problem with the mult... In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a （weakly） LU-efficient solution in the considered nonsmooth multiobjective programming problem with the multiple interval-objective function. Further, the sufficient optimality conditions for a （weakly） LU-efficient solution and several duality results in Mond-Weir sense are proved under assumptions that the functions constituting the considered nondifferentiable multiobjective programming problem with the multiple interval- objective function are convex. 展开更多
关键词 nonsmooth multiobjective programming problem with the multiple interval- objective function Fritz John necessary optimality conditions Karush-Kuhn- Tucker necessary optimality conditions （weakly） LU-efficient solution Mond- Weir duality
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FUZZY IDENTIFICATION METHOD BASED ON A NEW OBJECTIVE FUNCTION 认领 引用
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作者 王宏伟 贺汉根 黄柯棣 《Chinese Journal of Aeronautics》 EI CAS 2000年第3期162-166,共5页
A method of fuzzy identification based on a new objective function is proposed. The method could deal with the issue that input variables of a system have an effect on the input space while output variables of the sys... A method of fuzzy identification based on a new objective function is proposed. The method could deal with the issue that input variables of a system have an effect on the input space while output variables of the system do not exert an influence on the input space in the proposed objective functions of fuzzy clustering. The method could simultaneously solve the problems about structure identification and parameter estimation; thus it makes the fuzzy model become optimal. Simulation example demonstrates that the method could identify non linear systems and obviously improve modeling accuracy. 展开更多
关键词 objective function fuzzy clustering fuzzy identification non linear systems
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Randomized Objective Function Linear Programming in Risk Management 认领 引用 被引量：1
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作者 Dennis Ridley Felipe Llaugel +1 位作者 Inger Daniels Abdullah Khan 《Journal of Applied Mathematics and Physics》 2021年第3期391-402,共12页
The traditional linear programming model is deterministic. The way that uncertainty is handled is to compute the range of optimality. After the optimal solution is obtained, typically by the simplex method, one consid... The traditional linear programming model is deterministic. The way that uncertainty is handled is to compute the range of optimality. After the optimal solution is obtained, typically by the simplex method, one considers the effect of varying each objective function coefficient, one at a time. This yields the range of optimality within which the decision variables remain constant. This sensitivity analysis is useful for helping the analyst get a sense for the problem. However, it is unrealistic because objective function coefficients tend not to stand still. They are typically profit contributions from products sold and are subject to randomly varying selling prices. In this paper, a realistic linear program is created for simultaneously randomizing the coefficients from any probability distribution. Furthermore, we present a novel approach for designing a copula of random objective function coefficients according to a specified rank correlation. The corresponding distribution of objective function values is created. This distribution is examined directly for central tendency, spread, skewness and extreme values for the purpose of risk analysis. This enables risk analysis and business analytics, emerging topics in education and preparation for the knowledge economy. 展开更多
关键词 Linear Programming Random Objective Function Profit Distribution Risk Monte Carlo Simulation
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On the Optimization Problems with Continuity-type Objective Functions 认领 引用
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作者 LIANG Zhi-an 《内蒙古大学学报（自然科学版）》 CAS 北大核心 2016年第5期485-492,共8页
Multiohjective optimization problem(MP)and optimization problem with countably infinitely many objective functions(CIP)are extended to the op-timization problem with continuity-type objective funetions(CP).The related... Multiohjective optimization problem(MP)and optimization problem with countably infinitely many objective functions(CIP)are extended to the op-timization problem with continuity-type objective funetions(CP).The related concepts of efficient and properly efficient solutions are put forward,and some examples are given to show that it is a meaningful topic for theories and applications.Two related theorems about the efficient solutions and properly efficient solutions between CIP and CP are obtained. 展开更多
关键词 optimization continuity-type objective function efficient solution properly efficient solution
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Improving deconvolution reliability in well test analysis with an automated objective function 认领 引用
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作者 Mina S.Khalaf 《Deep Resources Engineering》 2026年第1期53-74,共22页
Deconvolution is a mathematical technique that eliminates the effects of production rate variations in pressure transient data,enabling the recovery of a smoother pressure signal extended across both drawdown and buil... Deconvolution is a mathematical technique that eliminates the effects of production rate variations in pressure transient data,enabling the recovery of a smoother pressure signal extended across both drawdown and buildup periods.This approach has distinct advantages over conventional analysis methods,including enhanced radius of investigation,improved derivative quality,and simplified use of existing interpretation techniques.Since the introduction of von Schroeter deconvolution method,as the first stable algorithm,in the early 2000s,several researchers have advanced the methodology by refining algorithms and improving the objective functions that govern their performance.Despite these developments,the definition of a robust and reliable objective function remains a challenge in achieving accurate deconvolution results.This study introduces a new objective function(NOF)for well test deconvolution that simplifies weighting schemes,eliminates subjective parameter tuning,and improves robustness under noisy conditions.Unlike earlier methods,the NOF assigns automated weights to pressure and rate measurements based on gauge accuracy,ensuring objective normalization of errors and removing the need for the unresolved flow rate regularization parameter.This streamlined approach not only reduces complexity but also enhances accuracy.The proposed noise-oriented NOF consistently outperformed traditional formulations across all simulated and field cases.In four synthetic examples with varying reservoir conditions and noise levels,the NOF successfully recovered smooth pressure responses and accurate flow rates,while the original von Schroeter and Levitan objective functions produced distorted or shifted signals and failed to adjust rates.Quantitative comparisons showed that this study produces a marked reduction in average deconvolution errors.This study enhances the stability and accuracy of deconvolution and offers a practical and superior tool for reservoir characterization,making it easier for engineers to extract meaningful reservoir properties,extend the radius of investigation,and reduce interpretation errors in real field applications. 展开更多
关键词 Pressure transient analysis Deconvolution Objective function optimization Reservoir characterization Measurements uncertainty
Experimental Evaluation of Objective Functions for Well-balanced Mapping 认领 引用
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作者 Chen Delai Xu Hong Zhou Ying and Zhang Defu 《Wuhan University Journal of Natural Sciences》 CAS 1996年第Z1期312-316,共5页
High performance of parallel computing on a message-passing multicomputer System relies on the balance of the workloads located on the processing elements of the System and the minimum communication ovcrheads among th... High performance of parallel computing on a message-passing multicomputer System relies on the balance of the workloads located on the processing elements of the System and the minimum communication ovcrheads among them. Mapping is the technology to partition the problem domain wellbalanced into multiple distinct execution tasks based on some measures. In mapping, a good objective function is the criterion to guarantce the distinct execution tasks equitable. In this paper, we evaluate five categories of those existed objective functions with three different problem subjects using experiments and find an objective function is much suitable for all kinds of problems. 展开更多
关键词 Mapping Heuristic algorithm Objective functions
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Modularity-like objective function in annotated networks 认领 引用 被引量：1
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作者 Jia-Rong Xie Bing-Hong Wang 《Frontiers of physics》 SCIE CSCD 2017年第6期109-113,共5页
We ascertain the modularity-like objective function whose optimization is equivalent to the maximum likelihood in annotated networks. We demonstrate that the modularity-like objective function is a lin- ear combinatio... We ascertain the modularity-like objective function whose optimization is equivalent to the maximum likelihood in annotated networks. We demonstrate that the modularity-like objective function is a lin- ear combination of modularity and conditional entropy. In contrast with statistical inference methods, in our method, the influence of the metadata is adjustable; when its influence is strong enough, the metadata can be recovered. Conversely, when it is weak, the detection may correspond to another partition. Between the two, there is a transition. This paper provides a concept for expanding the scope of modularity methods. 展开更多
关键词 community structure annotated networks modularity objective function
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Predictive control for greenhouse temperature and humidity and energy optimization by improved NMPC objective function algorithm 认领 引用
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作者 Lina Wang Ying Zhang +2 位作者 Mengjie Xu Qiuhui Liu Binrui Wang 《International Journal of Agricultural and Biological Engineering》 SCIE 2024年第5期128-136,共9页
Persistent low temperatures in autumn and winter have a huge impact on crops,and greenhouses rely on solar radiation and heating equipment to meet the required indoor temperature.But the energy cost of frequent operat... Persistent low temperatures in autumn and winter have a huge impact on crops,and greenhouses rely on solar radiation and heating equipment to meet the required indoor temperature.But the energy cost of frequent operation of the actuators is exceptionally high.The relationship between greenhouse environmental control accuracy and energy consumption is one of the key issues faced in greenhouse research.In this study,a non-linear model predictive control method with an improved objective function was proposed.The improved objective function used tolerance intervals and boundary constraints to optimize the objective evaluation.The nonlinear model predictive control(NMPC)controller design was based on the wavelet neural network(WNN)data-driven model and applied the interior point method to solve the optimal solution of the objective function control,thus balancing the contradiction between energy consumption and control precision.The simulation results showed that the improved NMPC method reduced energy consumption by 21.02%and 9.54%compared with the model predictive control and regular NMPC,which proved the method achieved good results in a low-temperature environment.This research can provide an important reference for the field as it offers a more efficient approach to managing greenhouse climates,potentially leading to substantial energy savings and enhanced sustainability in agricultural practices. 展开更多
关键词 greenhouse environmental control greenhouse energy optimization nonlinear model predictive control objective function improvement
Monthly Monetary Planning for China via Applying Method of Constructing Objective Function 认领 引用
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作者 ZENG Jian-hua, YANG Xiao-guang, XU Shan-ying Institute of Systems Science, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100080, China 《Journal of Systems Science and Systems Engineering》 SCIE 2001年第4期385-391,共7页
Many economic problems can be formulated as optimization problems. Econometricians have long devoted their efforts to construct the econometric equation systems, while the corresponding objective functions receive few... Many economic problems can be formulated as optimization problems. Econometricians have long devoted their efforts to construct the econometric equation systems, while the corresponding objective functions receive few attentions. In recent twenty years, some techniques to construct the objective functions with economic implications have been developed, which might have a potential in economic decision-making. In the paper we app1y the method of constructing objective function to design an optimization model for monthly monetary planning of China. The real monthly data from l991 to l999 are used to evaluate the monthly economic situation. Our empirical experiment shows that the model gives a good short-term forecasting. 展开更多
关键词 constructing objective function monetary planning optimization mode1
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Study on Heat Transfer in Double-Layer Topologically Optimized Microchannels under Non-Uniform Heat Sources in 2.5D Chips 认领 引用
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作者 Yechao Qin Zezhong Hou +2 位作者 Xiaojun Dai Zhenqian Chen Bo Xu 《Frontiers in Heat and Mass Transfer》 EI CAS 2026年第3期21-42,共22页
To address the increasing thermal management demands of electronic devices,this study proposes a single-inlet,single-outlet counterflow double-layer microchannel structure optimized for non-uniform heat sources and co... To address the increasing thermal management demands of electronic devices,this study proposes a single-inlet,single-outlet counterflow double-layer microchannel structure optimized for non-uniform heat sources and conducts a numerical analysis.The research focuses on designing a double-layer microchannel structure through topology optimization under 2.5D chip non-uniform heat source conditions.Its heat dissipation performance is compared with traditional linear microchannels to analyze the advantages of the topology-optimized microchannel.In a simulated 2.5D heat source scenario comprising a 240 W logic chip and four 40 W memory chips,the average temperature at the bottom of the topologically optimized microchannel heat sink decreased by 2 to 4 K compared to the conventional design when the inlet Reynolds number ranged from 500 to 2300.Concurrently,the system pressure drop was significantly reduced by 32%to 42%.These results demonstrate that this innovative design offers significant advantages in enhancing cooling efficiency and reducing energy consumption.Furthermore,due to its unique counter-current heat transfer mechanism,the structure also exhibits markedly improved temperature uniformity.This study provides an efficient design solution for advanced electronic thermal management scenarios characterized by constrained design space and stringent requirements for thermal stress management and integration density. 展开更多
关键词 Heat exchange maximization liquid cooled heat sink objective function topology optimization
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A compound objective reconfiguration of distribution networks using hierarchical encoded particle swarm optimization 认领 引用 被引量：3
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作者 WEN Juan TAN Yang-hong +1 位作者 JIANG Lin XU Zu-hua 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第3期600-615,共16页
With the development of automation in smart grids,network reconfiguration is becoming a feasible approach for improving the operation of distribution systems.A novel reconfiguration strategy was presented to get the o... With the development of automation in smart grids,network reconfiguration is becoming a feasible approach for improving the operation of distribution systems.A novel reconfiguration strategy was presented to get the optimal configuration of improving economy of the system,and then identifying the important nodes.In this strategy,the objectives increase the node importance degree and decrease the active power loss subjected to operational constraints.A compound objective function with weight coefficients is formulated to balance the conflict of the objectives.Then a novel quantum particle swarm optimization based on loop switches hierarchical encoded was employed to address the compound objective reconfiguration problem.Its main contribution is the presentation of the hierarchical encoded scheme which is used to generate the population swarm particles of representing only radial connected solutions.Because the candidate solutions are feasible,the search efficiency would improve dramatically during the optimization process without tedious topology verification.To validate the proposed strategy,simulations are carried out on the test systems.The results are compared with other techniques in order to evaluate the performance of the proposed method. 展开更多
关键词 distribution network reconfiguration node importance degree compound objective function hierarchical encoded
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Structural failure analysis with CMS-based ground motion selection using innovative cost function and weight factors 认领 引用
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作者 Delbaz Samadian Imrose B.Muhit Nashwan Dawood 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2024年第4期899-918,共20页
The selection and scaling of ground motion records is considered a primary and essential task in performing structural analysis and design.Conventional methods involve using ground motion models and a conditional spec... The selection and scaling of ground motion records is considered a primary and essential task in performing structural analysis and design.Conventional methods involve using ground motion models and a conditional spectrum to select ground motion records based on the target spectrum.This research demonstrates the influence of adopting different weighted factors for various period ranges during matching selected ground motions with the target hazard spectrum.The event data from the Next Generation Attenuation West 2(NGA-West 2)database is used as the basis for ground motion selection,and hazard de-aggregation is conducted to estimate the event parameters of interest,which are then used to construct the target intensity measure(IM).The target IMs are then used to select ground motion records with different weighted vector-valued objective functions.The weights are altered to account for the relative importance of IM in accordance with the structural analysis application of steel moment resisting frame(SMRF)buildings.Instead of an ordinary objective function for the matching spectrum,a novel model is introduced and compared with the conventional cost function.The results indicate that when applying the new cost function for ground motion selection,it places higher demands on structures compared to the conventional cost function.Moreover,submitting more weights to the first-mode period of structures increases engineering demand parameters.Findings demonstrate that weight factors allocated to different period ranges can successfully account for period elongation and higher mode effects. 展开更多
关键词 weighted objective function ground motion selection steel moment resisting frame hazard analysis
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Distributed Stochastic Optimization with Compression for Non-Strongly Convex Objectives 认领 引用
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作者 Xuanjie Li Yuedong Xu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第4期459-481,共23页
We are investigating the distributed optimization problem,where a network of nodes works together to minimize a global objective that is a finite sum of their stored local functions.Since nodes exchange optimization p... We are investigating the distributed optimization problem,where a network of nodes works together to minimize a global objective that is a finite sum of their stored local functions.Since nodes exchange optimization parameters through the wireless network,large-scale training models can create communication bottlenecks,resulting in slower training times.To address this issue,CHOCO-SGD was proposed,which allows compressing information with arbitrary precision without reducing the convergence rate for strongly convex objective functions.Nevertheless,most convex functions are not strongly convex(such as logistic regression or Lasso),which raises the question of whether this algorithm can be applied to non-strongly convex functions.In this paper,we provide the first theoretical analysis of the convergence rate of CHOCO-SGD on non-strongly convex objectives.We derive a sufficient condition,which limits the fidelity of compression,to guarantee convergence.Moreover,our analysis demonstrates that within the fidelity threshold,this algorithm can significantly reduce transmission burden while maintaining the same convergence rate order as its no-compression equivalent.Numerical experiments further validate the theoretical findings by demonstrating that CHOCO-SGD improves communication efficiency and keeps the same convergence rate order simultaneously.And experiments also show that the algorithm fails to converge with low compression fidelity and in time-varying topologies.Overall,our study offers valuable insights into the potential applicability of CHOCO-SGD for non-strongly convex objectives.Additionally,we provide practical guidelines for researchers seeking to utilize this algorithm in real-world scenarios. 展开更多
关键词 Distributed stochastic optimization arbitrary compression fidelity non-strongly convex objective function
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Overview of multi-objective optimization methods 认领 引用 被引量：2
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作者 LeiXiujuan ShiZhongke 《Journal of Systems Engineering and Electronics》 2004年第2期142-146,共5页
To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description ab... To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper. 展开更多
关键词 multi-objective optimization objective function Pareto optimality genetic algorithms simulated annealing fuzzy logical.
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