期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到22篇文章
< 1 2 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Low-Noise,High-Gain 28 GHz LNA Design Using Multi-Objective Optimization with NSGA-Ⅱ and MOPSO 认领 引用
1
作者 Spandana Saggurthi Anand Nayyar +1 位作者 Sk Hasane Ahammad Sumendra Yogarayan 《Computers, Materials & Continua》 SCIE EI 2026年第9期691-709,共19页
This work presents a multi-objective optimization framework for systematic design-space exploration of a 28 GHz single-stage cascode LNA(Low noise amplifier)in 22 nm FDSOI technology using NSGA-Ⅱ and MOPSO algorithms... This work presents a multi-objective optimization framework for systematic design-space exploration of a 28 GHz single-stage cascode LNA(Low noise amplifier)in 22 nm FDSOI technology using NSGA-Ⅱ and MOPSO algorithms.The objectives of the paper include simultaneous minimization of noise figure(NF)and power consumption while maximizing gain under matching and stability constraints.Using device parameters and circuit models that were developed for a 22 nm FDSOI process technology,an optimization framework was created in Python,with the passive components LG,LS,LD,LOUT,and COUT chosen to be the variables optimized.The NSGA-Ⅱ optimized design achieves 1.7 dB NF,17 dB gain,and 4.7 mW DC power,while MOPSO achieves 1.8 dB NF,17.1 dB gain,and 5.0 mW power.NSGA-Ⅱ provides improved Pareto diversity and slightly better output matching,whereas MOPSO reduces computational time by 24%with comparable RF performance.The results demonstrate effective multi-objective design-space exploration and controlled algorithm benchmarking at the schematic-level for mm-wave LNA design. 展开更多
关键词 LNA mm-wave multi-objective optimization NSGA-Ⅱ MOPSO internet of things(IoT) S-parameters gain and noise figure
暂未订购 下载PDF
Multi-objective optimal design of asymmetric base-isolated structures using NSGA-Ⅱ algorithm for improving torsional resistance 认领 引用
2
作者 Zhang Jiayu Qi Ai Yang Mianyue 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2025年第3期811-825,共15页
Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is... Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is cumbersome and inefficient.Thus,this work develops a multi-objective optimization method to enhance the torsional resistance of asymmetric base-isolated structures.The primary objective is to simultaneously minimize the interstory rotation of the superstructure,the rotation of the isolation layer,and the interstory displacement of the superstructure without exceeding the isolator displacement limits.A fast non-dominated sorting genetic algorithm(NSGA-Ⅱ)is employed to satisfy this optimization objective.Subsequently,the isolator arrangement,encompassing both positions and categories,is optimized according to this multi-objective optimization method.Additionally,an optimization design platform is developed to streamline the design operation.This platform integrates the input of optimization parameters,the output of optimization results,the finite element analysis,and the multi-objective optimization method proposed herein.Finally,the application of this multi-objective optimization method and its associated platform are demonstrated on two asymmetric base-isolated structures of varying heights and plan configurations.The results indicate that the optimal isolator arrangement derived from the optimization method can further improve the control over the lateral and torsional responses of asymmetric base-isolated structures compared to conventional conceptual design methods.Notably,the interstory rotation of the optimal base-isolated structure is significantly reduced,constituting only approximately 33.7%of that observed in the original base-isolated structure.The proposed platform facilitates the automatic generation of the optimal design scheme for the isolators of asymmetric base-isolated structures,offering valuable insights and guidance for the burgeoning field of intelligent civil engineering design. 展开更多
关键词 asymmetric base-isolated structures isolator arrangement multi-objective optimization NSGA-Ⅱalgorithm optimization design platform
暂未订购 下载PDF
Scaling the StrategyWall:Efficient Jailbreaking of LLMs via Component-Based Multi-Objective Optimization 认领 引用
3
作者 Jialing Tao Song Huang Changyou Zheng 《Computers, Materials & Continua》 SCIE EI 2026年第9期1054-1074,共21页
Background:Jailbreak attacks,which use crafted prompts to bypass safety alignments of Large Language Models(LLMs)and generate harmful content,pose a significant security threat.Existing methods often optimize for a si... Background:Jailbreak attacks,which use crafted prompts to bypass safety alignments of Large Language Models(LLMs)and generate harmful content,pose a significant security threat.Existing methods often optimize for a single objective(e.g.,attack success rate),neglecting critical factors like query efficiency,which limits their practicality and generalization.Methods:We propose a Componentized Multi-Objective Optimization Framework(CMOOF),which introduces a paradigm shift:it searches for generalizable and query-efficient attack strategy templates within a structured,component-based strategy space.CMOOF leverages the NSGA-Ⅱ algorithm to explicitly co-optimize two first-class objectives:Attack Success Rate(ASR)and Query Efficiency,thereby discovering their Pareto-optimal tradeoff frontier.Results:Experiments on benchmark datasets show significant improvements,with the highest jailbreak success rate reaching 98.75%on models like Llama3,and query efficiency surpassing baselines.Conclusions:CMOOF redefines jailbreak optimization from instance-level prompt crafting to strategy-level template discovery.The work provides an efficient,scalable,and generalizable jailbreak solution,and the framework offers broader insights for automated red teaming and LLM security defense. 展开更多
关键词 Jailbreak attacks LLMs multi-objective optimization NSGA-Ⅱ
暂未订购 下载PDF
A decoupled multi-objective optimization algorithm for cut order planning of multi-color garment 认领 引用
4
作者 DONG Hui LYU Jinyang +3 位作者 LIN Wenjie WU Xiang WU Mincheng HUANG Guangpu 《High Technology Letters》 EI CAS 2025年第1期53-62,共10页
This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is establish... This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is established with production error and production cost as optimization objectives,combined with constraints such as the number of equipment and the number of layers.Second,a decoupled multi-objective optimization algorithm(DMOA)is proposed based on the linear programming decoupling strategy and non-dominated sorting in genetic algorithmsⅡ(NSGAII).The size-combination matrix and the fabric-layer matrix are decoupled to improve the accuracy of the algorithm.Meanwhile,an improved NSGAII algorithm is designed to obtain the optimal Pareto solution to the MCOP problem,thereby constructing a practical intelligent production optimization algorithm.Finally,the effectiveness and superiority of the proposed DMOA are verified through practical cases and comparative experiments,which can effectively optimize the production process for garment enterprises. 展开更多
关键词 multi-objective optimization non-dominated sorting in genetic algorithmsⅡ(NSGAII) cut order planning(COP) multi-color garment linear programming decoupling strategy
暂未订购 下载PDF
Multi-Objective Optimization of Swirling Impinging Air Jets with Genetic Algorithm and Weighted Sum Method 认领 引用
5
作者 Sudipta Debnath Zahir Uddin Ahmed +3 位作者 Muhammad Ikhlaq Md.Tanvir Khan Avneet Kaur Kuljeet Singh Grewal 《Frontiers in Heat and Mass Transfer》 EI CAS 2025年第1期71-94,共24页
Impinging jet arrays are extensively used in numerous industrial operations,including the cooling of electronics,turbine blades,and other high-heat flux systems because of their superior heat transfer capabilities.Opt... Impinging jet arrays are extensively used in numerous industrial operations,including the cooling of electronics,turbine blades,and other high-heat flux systems because of their superior heat transfer capabilities.Optimizing the design and operating parameters of such systems is essential to enhance cooling efficiency and achieve uniform pressure distribution,which can lead to improved system performance and energy savings.This paper presents two multi-objective optimization methodologies for a turbulent air jet impingement cooling system.The governing equations are resolved employing the commercial computational fluid dynamics(CFD)software ANSYS Fluent v17.The study focuses on four controlling parameters:Reynolds number(Re),swirl number(S),jet-to-jet separation distance(Z/D),and impingement height(H/D).The effects of these parameters on heat transfer and impingement pressure distribution are investigated.Non-dominated Sorting Genetic Algorithm(NSGA-II)and Weighted Sum Method(WSM)are employed to optimize the controlling parameters for maximum cooling performance.The aim is to identify optimal design parameters and system configurations that enhance heat transfer efficiency while achieving a uniform impingement pressure distribution.These findings have practical implications for applications requiring efficient cooling.The optimized design achieved a 12.28%increase in convective heat transfer efficiency with a local Nusselt number of 113.05 compared to 100.69 in the reference design.Enhanced convective cooling and heat flux were observed in the optimized configuration,particularly in areas of direct jet impingement.Additionally,the optimized design maintained lower wall temperatures,demonstrating more effective thermal dissipation. 展开更多
关键词 Jet impingement multi-objective optimization pareto front NSGA-Ⅱ WSM
暂未订购 下载PDF
Multi-Objective Optimization on Dynamic Response of Solenoid Switching Valve 认领 引用 被引量：1
6
作者 Mingjun Qiu Jun Hong +3 位作者 Jing Yao Pei Wang Qiyin Lin Bo Ning 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2025年第6期584-601,共18页
The solenoid switching valve(SSV)is the key control component of heavy equipment such as continuous casting machines.However,the incompatibility of structural parameters increases the opening and closing time of the S... The solenoid switching valve(SSV)is the key control component of heavy equipment such as continuous casting machines.However,the incompatibility of structural parameters increases the opening and closing time of the SSV.Therefore,this study proposes an optimized design method for an SSV to improve its dynamic performance.First,a multi-physics field-coupling model of the SSV is built,and the effects of different structural parameters on the electromagnetic characteristics are analyzed.After identifying the key influencing parameters,second-order response surface models are established to efficiently predict the opening and closing time.Subsequently,based on the nondominated sorting genetic algorithmⅡ(NSGA-Ⅱ),multi-objective optimization is applied to obtain the Pareto optimal solution of the structural parameters under the double-voltage driving strategy.The structure of the solenoid and valve as well as the dynamic characteristics of the valve are improved.Compared with those before optimization,the optimization results show that the opening and closing time of the optimized SSV are reduced by 24.38%and 51.8%,respectively,and the volume is reduced by 19.7%.The research results and the influence of the solenoid structural parameters on the electromagnetic force provide significant guidance for the design of this type of valve. 展开更多
关键词 Solenoid switching valve Dynamic response Response surface prediction model NSGA-Ⅱ Multi-objective optimization Structure improvement
暂未订购 下载PDF
Multi-objective Function Optimization for Environmental Control of a Greenhouse Based on a RBF and NSGA-Ⅱ 认领 引用
7
作者 Zhou Xiu-li Liu Ming-wei +3 位作者 Wang Ling Xu Xiao-chuan Chen Gang Wang De-fu 《Journal of Northeast Agricultural University(English Edition)》 CAS 2021年第1期75-89,共15页
To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solve... To better meet the needs of crop growth and achieve energy savings and efficiency enhancements,constructing a reliable environmental model to optimize greenhouse decision parameters is an important problem to be solved.In this work,a radial-basis function(RBF)neural network was used to mine the potential changes of a greenhouse environment,a temperature error model was established,a multi-objective optimization function of energy consumption was constructed and the corresponding decision parameters were optimized by using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-Ⅱ).The simulation results showed that RBF could clarify the nonlinear relationship among the greenhouse environment variables and decision parameters and the greenhouse temperature.The NSGA-Ⅱcould well search for the Pareto solution for the objective functions.The experimental results showed that after 40 min of combined control of sunshades and sprays,the temperature was reduced from 31℃to 25℃,and the power consumption was 0.5 MJ.Compared with tire three days of July 24,July 25 and July 26,2017,the energy consumption of the controlled production greenhouse was reduced by 37.5%,9.1%and 28.5%,respectively. 展开更多
关键词 greenhouse temperature multi-objective optimization radial-basis function(RBF) non-dominated sorting genetic algorithm with an elite strategy(NSGA-Ⅱ)
暂未订购 下载PDF
Optimising PID Controllers for Multi-Area Automatic Generation Control With Improved NSGA-Ⅱ 认领 引用
8
作者 Yang Yang Yuchao Gao +1 位作者 Shangce Gao Jinran Wu 《CAAI Transactions on Intelligence Technology》 SCIE EI CSCD 2025年第4期1135-1147,共13页
Modern automated generation control(AGC)is increasingly complex,requiring precise frequency control for stability and operational accuracy.Traditional PID controller optimisation methods often struggle to handle nonli... Modern automated generation control(AGC)is increasingly complex,requiring precise frequency control for stability and operational accuracy.Traditional PID controller optimisation methods often struggle to handle nonlinearities and meet robustness requirements across diverse operational scenarios.This paper introduces an enhanced strategy using a multi-objective optimisation framework and a modified non-dominated sorting genetic algorithm Ⅱ(SNSGA).The proposed model optimises the PID controller by minimising key performance metrics:integration time squared error(ITSE),integration time absolute error(ITAE),and rate of change of deviation(J).This approach balances convergence rate,overshoot,and oscillation dynamics effectively.A fuzzy-based method is employed to select the most suitable solution from the Pareto set.The comparative analysis demonstrates that the SNSGA-based approach offers superior tuning capabilities over traditional NSGA-Ⅱ and other advanced control methods.In a two-area thermal power system without reheat,the SNSGA significantly reduces settling times for frequency deviations:2.94s for Δf1 and 4.98s for Δf2,marking improvements of 31.6%and 13.4%over NSGA-Ⅱ,respectively. 展开更多
关键词 automatic generation control load frequency control multi-objective optimization nondominated sorting genetic algorithmⅡ PID controller
暂未订购 下载PDF
Multi-objective Optimization of Industrial Purified Terephthalic Acid Oxidation Process 认领 引用 被引量：13
9
作者 牟盛静 苏宏业 +1 位作者 古勇 褚健 《Chinese Journal of Chemical Engineering》 SCIE EI CAS 2003年第5期536-541,共6页
Multi-objective optimization of a purified terephthalic acid (PTA) oxidation unit is carried out in this paper by using a process modei that has been proved to describe industrial process quite well. The modei is a se... Multi-objective optimization of a purified terephthalic acid (PTA) oxidation unit is carried out in this paper by using a process modei that has been proved to describe industrial process quite well. The modei is a semi-empirical structured into two series ideal continuously stirred tank reactor (CSTR) models. The optimal objectives include maximizing the yield or inlet rate and minimizing the concentration of 4-carboxy-benzaldhyde, which is the main undesirable intermediate product in the reaction process. The multi-objective optimization algorithra applied in this study is non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ). The performance of NSGA-Ⅱ is further illustrated by application to the title process. 展开更多
关键词 multi-objective optimization purified terephthalic acid oxidation process non-dominated sorting genetic algorithm Ⅱ
暂未订购 下载PDF
Multi-objective capacity allocation optimization method of photovoltaic EV charging station considering V2G 认领 引用 被引量：10
10
作者 ZHENG Xue-qin YAO Yi-ping 《Journal of Central South University》 SCIE EI CAS CSCD 2021年第2期481-493,共13页
Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed... Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency. 展开更多
关键词 vehicle to grid (V2G) capacity configuration optimization time-to-use (TOU) price multi-objective optimization NSGA-Ⅱ algorithm NSGA-SA algorithm
暂未订购 下载PDF
Multi-objective optimization of methane production system from biomass through anaerobic digestion 认领 引用 被引量：1
11
作者 Weijun Li Jakob Kj?bsted Huusom +3 位作者 Zhimao Zhou Yi Nie Yajing Xu Xiangping Zhang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2018年第10期2084-2092,共9页
This work addressed the multi-objective optimization of a biogas production system considering both environmental and economic criteria. A mixed integer non-linear programming(MINLP) model was established and solved w... This work addressed the multi-objective optimization of a biogas production system considering both environmental and economic criteria. A mixed integer non-linear programming(MINLP) model was established and solved with non-dominated sorting genetic algorithm Ⅱ, from which the Pareto fronts, the optimal technology combinations and operation conditions were obtained and analyzed. It's found that the system is feasible in both environmental and economic considerations after optimization. The most expensive processing section is decarbonization; the most expensive equipment is anaerobic digester; the most power-consuming processing section is digestion, followed by decarbonization and waste management. The positive green degree value on the process is attributed to processing section of digestion and waste management. 3:1 chicken feces and corn straw, solar energy, pressure swing adsorption and 3:1 chicken feces and rice straw, solar energy, pressure swing adsorption are turned out to be two robust technology combinations under different prices of methane and electricity by sensitivity analysis. The optimization results provide support for optimal design and operation of biogas production system considering environmental and economic objectives. 展开更多
关键词 Biogas production system MINLP Multi-objective optimization Non-dominated sorting genetic algorithm Ⅱ Green degree value
暂未订购 下载PDF
Multi-objective optimization design for leg mechanism of hydraulic-actuated quadruped robot 认领 引用 被引量：1
12
作者 马明 孙博 +1 位作者 王建中 施家栋 《Journal of Beijing Institute of Technology》 EI CAS 2013年第1期12-19,共8页
In order to improve the robot＇ s abilities of bearing heavy burdens and transporting in complex terrains, the multi-objective optimization design for leg mechanism of the quadruped robot with hydraulic actuated is st... In order to improve the robot＇ s abilities of bearing heavy burdens and transporting in complex terrains, the multi-objective optimization design for leg mechanism of the quadruped robot with hydraulic actuated is studied in this paper. The kinematics and dynamics of the robot are ana- lyzed and the two-dimensional linear inverted pendulum model is adopted in planning the trajectories of joints. Then the mathematical model of valve-controlled asymmetric cylinder and control model of single leg are proposed respectively. In the end, NSGA-Ⅱ algorithm is used to achieve the multi^ob- jective optimization design of parameters concerning single leg mechanism and PD torque control. The results prove that the optimized leg mechanism can significantly reduce the required maximum power of hydraulic system, thus decrease its own weight and lead to the obtaining of good dynamic performance. 展开更多
关键词 quadruped robot multi-objective optimization NSGA-Ⅱ algorithm torque control
暂未订购 下载PDF
Multi-objective Dimensional Optimization of a 3-DOF Translational PKM Considering Transmission Properties 认领 引用 被引量：1
13
作者 Song Lu Yang-Min Li Bing-Xiao Ding 《International Journal of Automation and computing》 CSCD 2019年第6期748-760,共13页
Multi-objective dimensional optimization of parallel kinematic manipulators(PKMs) remains a challenging and worthwhile research endeavor. This paper presents a straightforward and systematic methodology for implementi... Multi-objective dimensional optimization of parallel kinematic manipulators(PKMs) remains a challenging and worthwhile research endeavor. This paper presents a straightforward and systematic methodology for implementing the structure optimization analysis of a 3-prismatic-universal-universal(PUU) PKM when simultaneously considering motion transmission, velocity transmission and acceleration transmission. Firstly, inspired by a planar four-bar linkage mechanism, the motion transmission index of the spatial parallel manipulator is based on transmission angle which is defined as the pressure angle amongst limbs. Then, the velocity transmission index and acceleration transmission index are derived through the corresponding kinematics model. The multi-objective dimensional optimization under specific constraints is carried out by the improved non-dominated sorting genetic algorithm(NSGA Ⅱ), resulting in a set of Pareto optimal solutions. The final chosen solution shows that the manipulator with the optimized structure parameters can provide excellent motion, velocity and acceleration transmission properties. 展开更多
关键词 Multi-objective optimization parallel kinematic manipulator transmission property non-dominated sorting genetic algorithm(NSGA Ⅱ)
暂未订购 下载PDF
Optimization of drag embedment anchors applying multi-objective evolutionary algorithm NSGA-Ⅱ 认领 引用
14
作者 Kacper Cerek Elnaz Hadjiloo +1 位作者 Jürgen Grabe Duy Anh Dao 《Journal of Ocean Engineering and Science》 SCIE CSCD 2025年第6期1019-1030,共12页
Establishing renewables on a floating platform in the deep sea needs secure anchoring to the seabed,commonly achieved with drag embedment anchors(DEAs).The conventional design process relies heavily on empirical testi... Establishing renewables on a floating platform in the deep sea needs secure anchoring to the seabed,commonly achieved with drag embedment anchors(DEAs).The conventional design process relies heavily on empirical testing and is often time and resource-intensive,potentially leading to suboptimal designs.This research aims to overcome these limitations by applying an evolutionary optimization algorithm to existing analytical solutions for DEAs,identifying optimal anchor fluke and shank lengths.By leveraging an optimization strategy,we aim to enhance the design process while diminishing the dependency on exhaustive physical testing and high computational cost.We employ the Non-Dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ)to optimize anchor shapes,with a focus on three key objectives:maximizing embedment depth and bearing capacity,and minimizing anchor volume.The methodology presents a Pareto front,encompassing all optimal solutions based on the formulated objectives,and demonstrates the efficiency of NSGA-Ⅱ as a tool for optimizing anchor shapes. 展开更多
关键词 Drag embedment anchor Multi-objective optimization Floating renewables NSGA-Ⅱ Sustainable design
Models for Location Inventory Routing Problem of Cold Chain Logistics with NSGA-Ⅱ Algorithm 认领 引用 被引量：3
15
作者 郑建国 李康 伍大清 《Journal of Donghua University(English Edition)》 CAS 2017年第4期533-539,共7页
In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location... In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location,inventory and transportation.Due to the complex of LIR problem( LIRP), a multi-objective genetic algorithm(GA), non-dominated sorting in genetic algorithm Ⅱ( NSGA-Ⅱ) has been introduced. Its performance is tested over a real case for the proposed problems. Results indicate that NSGA-Ⅱ provides a competitive performance than GA,which demonstrates that the proposed model and multi-objective GA are considerably efficient to solve the problem. 展开更多
关键词 cold chain logistics multi-objective location inventory routing problem(LIRP) non-dominated sorting in genetic algorithm Ⅱ(NSGA-Ⅱ)
暂未订购 下载PDF
Optimization of Cutting Parameters for Trade-off Among Carbon Emissions, Surface Roughness, and Processing Time 认领 引用 被引量：7
16
作者 Zhipeng Jiang Dong Gao +1 位作者 Yong Lu Xianli Liu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2019年第6期124-141,共18页
As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is ... As the manufacturing industry is facing increasingly serious environmental problems, because of which carbon tax policies are being implemented, choosing the optimum cutting parameters during the machining process is crucial for automobile panel dies in order to achieve synergistic minimization of the environment impact, product quality, and processing efficiency. This paper presents a processing task-based evaluation method to optimize the cutting parameters, considering the trade-off among carbon emissions, surface roughness, and processing time. Three objective models and their relationships with the cutting parameters were obtained through input–output, response surface, and theoretical analyses, respectively. Examples of cylindrical turning were applied to achieve a central composite design(CCD), and relative validation experiments were applied to evaluate the proposed method. The experiments were conducted on the CAK50135 di lathe cutting of AISI 1045 steel, and NSGA-Ⅱ was used to obtain the Pareto fronts of the three objectives. Based on the TOPSIS method, the Pareto solution set was ranked to find the optimal solution to evaluate and select the optimal cutting parameters. An S/N ratio analysis and contour plots were applied to analyze the influence of each decision variable on the optimization objective. Finally, the changing rules of a single factor for each objective were analyzed. The results demonstrate that the proposed method is effective in finding the trade-off among the three objectives and obtaining reasonable application ranges of the cutting parameters from Pareto fronts. 展开更多
关键词 Automobile panel dies Carbon emission Parameter optimization Multi-objective optimization NSGA-Ⅱ
暂未订购 下载PDF
GIS spatial optimization for agricultural crop allocation using NSGA-Ⅱ 认领 引用 被引量：2
17
作者 Tipaluck Krityakierne Pornpimon Sinpayak Noppadon Khiripet 《Information Processing in Agriculture》 SCIE EI CSCD 2025年第2期139-150,共12页
This study focuses on the shift from traditional farming methods,reliant on farmer intuition and manual processes,to modern,automated approaches crucial for Thailand’s agricultural sustainability.Despite its vital ro... This study focuses on the shift from traditional farming methods,reliant on farmer intuition and manual processes,to modern,automated approaches crucial for Thailand’s agricultural sustainability.Despite its vital role in the country’s economy,outdated practices lead to supply imbalances and perpetuate poverty among smallholder farmers.Using geographic information systems(GIS)and mathematical optimization,the present study aims to determine optimal agricultural crop allocation.A multi-objective optimization crop spatial allocation model leverages geospatial data,including crop,soil and climate suitability,to enhance the accuracy of our model.Additionally,we incorporate agricultural economics data,such as market price,crop yield,production cost,distances to secondary producers,production budget limitations,and minimum crop production requirements.To speedup the convergence of the algorithm,we introduce more suitable crossover and mutation operators in NSGA-Ⅱ,aiming to direct the search towards the Pareto optimal solutions.We demonstrate the effectiveness of our approach in a case study of the agricultural area in Chiang Mai province,Thailand,focusing on three major industrial crops:corn,cane,and rice.Our model suggests land allocation that adheres to both the budget constraint and the minimum production requirements,while retaining only a small surplus for each crop.The successful implementation of this approach in our case study marks a significant advancement in Thai agricultural research,paving the way for long-term economic and environmental sustainability. 展开更多
关键词 Crop allocation Evolutionary algorithm GIS Multi-objective Spatial optimization NSGA-Ⅱ
An improved multi-objective method for the selection of driverless taxi site locations 认领 引用
18
作者 Yaqin He Yu Xiao +1 位作者 Jiehang Chen Daobin Wang 《International Journal of Transportation Science and Technology》 EI CSCD 2025年第2期387-402,共16页
To expedite the large-scale deployment of driverless taxis and advance the autonomous driving industry,research on the location of integrated parking and charging facilities for driverless taxis has emerged as a signi... To expedite the large-scale deployment of driverless taxis and advance the autonomous driving industry,research on the location of integrated parking and charging facilities for driverless taxis has emerged as a significant issue in urban traffic.This study employs a progressive"preliminary selection-screening-optimal selection"approach for site selec-tion.First,the preliminary selection of parking sites is conducted by clustering various point-of-interest types.Subsequently,a multi-objective site selection model is developed to maximize the coverage of demand points,minimize construction costs,address the lar-gest population demands,and minimize the distance between demand points and candi-date sites.The non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)is adopted to obtain several Pareto optimal solutions.The evaluation indexes are selected according to opera-tors,users,and the public transport system to estimate the Pareto optimal solutions,and then the final location solution can be obtained.The calculation methods for several key parameters are improved during the modeling process.Location potential and location influence coefficient are selected to adjust the number of driverless taxi parking spaces.Additionally,isochrones drawn based on the actual road network and path planning repre-sent the service range of candidate points.Meanwhile,distance based on actual road net-work rather than Euclidean distance is introduced to calculate the distance between candidate points.Finally,a case study shows that the method proposed in this study could reduce the total initial travel time to reach the demand points by 64%,which is indepen-dent of operational scheduling. 展开更多
关键词 Urban traffic Parking site selection Non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ) Driverless taxi Multi-objective location model
汽车磁流变阻尼器多目标优化分析(英文) 认领 引用
19
作者 邓国红 李飞 +2 位作者 杨鄂川 欧健 张勇 《机床与液压》 北大核心 2015年第24期34-39,共6页
为了改善汽车的被动安全性能,提出将一种单杆单筒式磁流变阻尼器应用于汽车前部吸能结构中。提出以修正Bingham塑性模型(BPM模型)为理论基础,以最大阻尼力和可调范围为优化目标,运用mode FRONTIER自带的非支配排序遗传算法(NSGA-II)对... 为了改善汽车的被动安全性能,提出将一种单杆单筒式磁流变阻尼器应用于汽车前部吸能结构中。提出以修正Bingham塑性模型(BPM模型)为理论基础,以最大阻尼力和可调范围为优化目标,运用mode FRONTIER自带的非支配排序遗传算法(NSGA-II)对所采用的磁流变阻尼器结构参数进行多目标优化分析。优化结果表明:最大阻尼力和可调范围成反比,所用的优化算法不可能使两个优化目标同时达到最优,只能在众多前沿解中选择符合条件的优化解。优化后的磁流变阻力器磁场分布更加集中合理。 展开更多
关键词 Magnetorheological damper, Multi-objective optimization, BPM model, The NSGA Ⅱ algorithm
暂未订购 下载PDF
Multiobjective car relocation problem in one-way carsharingsystem 认领 引用
20
作者 Rabih Zakaria Mohammad Dib Laurent Moalic 《Journal of Modern Transportation》 2018年第4期297-314,共18页
In this paper, we present a multiobjective approach for solving the one-way car relocation problem.We fix three objectives that include the number of remaining rejected demands, the number of jockeys used for the relo... In this paper, we present a multiobjective approach for solving the one-way car relocation problem.We fix three objectives that include the number of remaining rejected demands, the number of jockeys used for the relocation operations, and the total time used by these jockeys. For this sake, we propose to apply two algorithms namely NSGA-Ⅱ and an adapted memetic algorithm(MA) that we call MARPOCS which stands for memetic algorithm for the one-way carsharing system. The NSGA-Ⅱ is used as a reference to compare the performance of MARPOCS. The comparison of the approximation sets obtained by both algorithms shows that the hybrid algorithm outperforms the classical NSGA-Ⅱ and so solutions generated by the MARPOCS are much better than the solutions generated by NSGA-Ⅱ. This observation is proved by the comparison of different quality indicators’ values that are used to compare the performance of each algorithm. Results show that the MARPOCS is promising to generate very good solutions for the multiobjective car relocation problem in one-way carsharing system. It shows a good performance in exploring the search space and in finding solution with very good fitness values. 展开更多
关键词 Carsharing Car relocation Integer linear programming(ILP) Multiobjective optimization Memetic algorithm NSGA-Ⅱ
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈