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multi-objective optimization of active steering system with force and displacement coupled control

Journal of Central South University 2012年第4期19卷 974-981页

作者：赵万忠孙培坤刘顺林逸 epartment of Vehicle Engineering Nanjing University of Aeronautics and Astronautics State Key Laboratory of Mechanical Transmission Chongqing University Department of Vehicle Engineering Nanjing University of Aeronautics and Astronautics School of Mechanical and Vehicular Engineering Beijing Institute of Technology

A novel active steering system with force and displacement coupled control(the novel AFS system) was introduced,which has functions of both the active steering and electric power *** on the model of the novel AFS system and the vehicle three-degree of freedom system,the concept and quantitative formulas of the novel AFS system steering performance were *** steering road feel and steering portability were set as the optimizing targets with the steering stability and steering portability as the constraint *** to the features of constrained optimization of multi-variable function,a multi-variable genetic algorithm for the system parameter optimization was *** simulation results show that based on parametric optimization of the multi-objective genetic algorithm,the novel AFS system can improve the steering road feel,steering portability and steering stability,thus the optimization method can provide a theoretical basis for the design and optimization of the novel AFS system.

关键词： vehicle engineering active steering electric power steering multi-objective genetic algorithm

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Class-weighted neural network for monotonic imbalanced classification

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2021年第4期12卷 1191-1201页

作者： Zhu, Hong Liu, Han Fu, Aimin Shenzhen Univ Guangdong Key Lab Intelligent Informat Proc Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China Hebei Univ Sch Math & Informat Sci Baoding 071000 Peoples R China

In real life scenarios, classification problems with the characters of monotonicity constraints and imbalanced class distribution widely exist. However, at present, the research on this kind of problem is still rare. Traditional algorithms designed only for monotonic classification and imbalanced classification are not available for monotonic imbalanced classification. So far, there is only one approach specially designed for monotonic imbalanced classification problems, which is based on the resampling technique. In this paper, from the algorithmic point of view, we propose a weighted single-hidden-layer feedforward neural network (WMCS-SLFN) based on multi-objective genetic algorithm, where both the monotonicity constraints and the imbalanced distribution are considered. Additionally, in order to improve the generalization capability of WMCS-SLFN, we put forward a selective ensemble strategy for WMCS-SLFN based on the 0-1 knapsack problem, which can generate an ensemble of WMCS-SLFN with the optimal prediction accuracy under the monotonicity constraints. Contrast experiments conducted on eight monotonic imbalanced datasets verify the effectiveness of our proposed methods, and moreover, the experimental results analyzed by Wilcoxon statistical test highlight the advantage of our work significantly.

关键词： Monotonic classification Imbalanced classfication Cost-sensitive learning multi-objective genetic algorithm 0– 1 knapsack problem

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Optimization of zigzag flow channels of a printed circuit heat exchanger for nuclear power plant application

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JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY 2012年第3期49卷 343-351页

作者： Lee, Sang-Moon Kim, Kwang-Yong Inha Univ Dept Mech Engn Inchon 402751 South Korea

Printed circuit heat exchanger (PCHE) is recently considered as a recuperator for the high-temperature gas cooled reactor. In this study, shape optimization of zigzag flow channels in a PCHE has been performed to enhance heat transfer performance and reduce the friction loss based on three-dimensional Reynolds-averaged Navier-Stokes analysis with the Shear Stress Transport Turbulence model. A multiobjective genetic algorithm is used for the multi-objective optimization. Two non-dimensional objective functions related to heat transfer performance and friction loss are employed. The shape of a flow channel is defined by two geometric design variables, viz. the cold channel angle and the ellipse aspect ratio of the cold channel. The experimental points within the design space are selected using Latin hypercube sampling as the design of the experiment. The response surface approximation model is used to approximate the Pareto-optimal front. Five optimal designs on the Pareto-optimal front have been selected using k-means clustering. The flow and heat transfer characteristics, as well as the objective function values, of these designs have been compared with those of the reference design.

关键词： printed circuit heat exchanger design optimization multi-objective genetic algorithm Reynolds-averaged Navier-Stokes analysis shear stress transport model

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Fluid-thermal-structural analysis and structural optimization of spiral-wound heat exchanger

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2018年 95卷 42-52页

作者： Wang, Simin Jian, Guanping Xiao, Juan Wen, Jian Zhang, Zaoxiao Tu, Jiyuan Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Shanxi Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Shaanxi Peoples R China Tsinghua Univ Minist Educ Key Lab Adv Reactor Engn & Safety Inst Nucl & New Energy Technol Beijing 100084 Peoples R China

Based on the liquid-solid-thermal coupling method, the effects of configuration parameters on the flow characteristic, the heat transfer performance and the stress distribution on the tube bundle of spiral-wound heat exchanger (SWHE) were numerically studied. The results show that the shell-side flow patterns change from cross flow into oblique flow and the overall heat transfer coefficient increases firstly and then decreases with the increase of the wingding angle. The maximum stress intensity decreases firstly with the increase of the inlet flow rate and then decreases. The thermal stress takes a leading position in the tube bundle stress distribution attributed to the higher heat transfer temperature difference. With the inlet flow rate increasing, the heat transfer is enhanced and the temperature difference decreases which result in the decrease of the proportion of thermal stress and the increase of the impact of the primary stress. The optimal structure was obtained by the multi-objective genetic algorithm based on the genetic Aggregation response surface. Compared with the original structure, the average comprehensive performance of three optimal candidates of SWHE increase by 57.64% and the maximum stresses intensity of the tube bundle are far less than the material allowable stress.

关键词： Spiral-wound heat exchanger Fluid-thermal-structural analysis Parametric modeling multi-objective genetic algorithm

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A real-time forecasting model for the spatial distribution of typhoon rainfall

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JOURNAL OF HYDROLOGY 2015年 521卷 302-313页

作者： Lin, Gwo-Fong Jhong, Bing-Chen Natl Taiwan Univ Dept Civil Engn Taipei 10617 Taiwan

Accurate forecasts of hourly rainfall are necessary for early warning systems during typhoons. In this paper, a typhoon rainfall forecasting model is proposed to yield 1- to 6-h ahead forecasts of hourly rainfall. First, an input optimization step integrating multi-objective genetic algorithm (MOGA) with support vector machine (SVM) is developed to identify the optimal input combinations. Second, based on the results of the first step, the forecasted rainfall from each station is used to obtain the spatial characteristics of the rainfall process is presented. An actual application to Tsengwen river basin is conducted to demonstrate the advantage of the proposed model. The results clearly indicate that the proposed model effectively improves the forecasting performance and decreases the negative impact of increasing forecast lead time. The optimal input combinations can be obtained from the proposed model for different stations with different geographical conditions. In addition, the proposed model is capable of producing more acceptable the results of rainfall maps than other model. In conclusion, the proposed modeling technique is useful to improve the hourly typhoon rainfall forecasting and is expected to be helpful to support disaster warning systems. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Hourly typhoon rainfall forecasting Spatial characteristics Meteorological data multi-objective genetic algorithm Support vector machine

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QuESt: a QoS-based energy efficient sensor routing protocol

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WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2009年第3期9卷 417-426页

作者： Saxena, Navrati Roy, Abhishek Shin, Jitae Sungkyunkwan Univ Sch Informat & Commun Engn Suwon 440746 South Korea Samsung Elect WiBro Syst Lab Suwon South Korea

Rapid penetration of smart wireless devices and enormous growth of wireless communication technologies has already set the stage for deployment of wireless sensor networks (WSNs). While these small sensor nodes are often considered as the future of wireless communications, they also Suffer from energy constraints. On the other hand. with increasing demand for real-time services in next generation wireless networks, quality-of-service (QoS)-based routing has emerged as an interesting research topic. Naturally offering some QoS-guarantee in sensor networks raises significant challenges. The network needs to cope up with battery-constraints, while providing precise QoS (end-to-end delay and bandwidth requirement) guarantee. More precisely, designing such QoS-protocols, optimizing multiple objectives, is computationally intractable. Based on the multi-objective genetic algorithm (MOGA), in this paper we propose a QoS-based energy-efficient sensor rowing (QuESt) protocol that determines application-specific, near-optimal sensory-routes demand, by optimizing multiple QoS parameters, (end-to-end delay and bandwidth requirements) and energy consumption. Simulation results demonstrate that the proposed protocol is capable of discovering a set of QoS-based, near-optimal routes, even with imprecise network information. Copyright (C) 2007 John Wiley & Sons, Ltd.

关键词： sensor networks multi-objective genetic algorithm QoS routing

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A multi-objective mathematical model for cellular manufacturing systems design with probabilistic demand and machine reliability analysis

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第5-8期75卷 755-770页

作者： Aghajani, Aydin Didehbani, Saeid Ahmadi Zadahmad, Manouchehr Seyedrezaei, Mir Hasan Mohsenian, Omid Islamic Azad Univ Ilkhchi Branch Dept Comp Engn Ilkhchi Iran Payame Noor Univ Dept Ind Engn Tehran Iran Univ Illinois Dept Mech & Ind Engn Chicago IL 60607 USA

This paper presents a dynamic multi-objective mixed integer mathematical model for cell formation problem with probabilistic demand and machine reliability analysis, where the total system costs, machine underutilization cost, and maximum system failure rate over the planning time periods are to be minimized simultaneously. The total system cost objective function calculates machine operating, internal part production, intercellular material handling, and subcontracting costs. Since in this type of problems, objectives are in conflict with each other, so finding an ideal solution (a solution that satisfies all objectives simultaneously) is not possible. Therefore, this study uses the augmented epsilon-constraint method (to solve small size problems) and a nondominated sorting genetic algorithm (NSGAII) (to solve large size problems) to find the Pareto optimal frontier that decision makers can select her/his preferred solution. Numerical examples will be solved to demonstrate the efficiency of the proposed algorithm.

关键词： Group technology Dynamic probabilistic demand multi-objective mathematical model Pareto optimal Exponential distribution Machine reliability Machine availability Poisson distribution multi-objective genetic algorithm

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Demand-oriented multi-objective planning method for electronic product technology development

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APPLIED MATHEMATICAL MODELLING 2016年第5-6期40卷 3620-3634页

作者： Chiang, Tzu-An Che, Z. H. Wang, Te-Wei Chen, Jian-Hong Natl Taipei Univ Business Dept Business Adm 321Sect 1Jinan Rd Taipei Taiwan Natl Taipei Univ Technol Dept Ind Engn & Management 1Sect 3Zhongxiao E Rd Taipei 106 Taiwan Univ Illinois Dept Management Informat Syst One Univ Plaza Springfield IL 62703 USA Natl Taipei Univ Technol Dept Ind Engn & Management 1Sect 3Zhongxiao E Rd Taipei 106 Taiwan

In this study, a demand-oriented multi-objective planning method is proposed for electronic product technology development. The proposed method uses the analytical hierarchy process to analyze the relative importance of each customer demand. Subsequently, quality function deployment is used to analyze the relationships between customer demands and product technologies, as well as for evaluating the customer satisfaction level for each electronic product that is being implemented. By using a model to identify the life-cycle stage of the product technology, each electronic product technology is classified in order to determine how to obtain the technology. A multi-objective evaluation model of planning strategies is obtained for electronic product technology development to evaluate the performance of different planning strategies. A multi-objective genetic algorithm is utilized to help companies efficiently establish an optimal planning strategy for electronic product technology development with the maximum customer satisfaction level and minimum product development cost. Finally, a case study of a green smart phone development project is provided to demonstrate and verify the practical contributions of the proposed method. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Electronic product technology development Life-cycle stage of product technology multi-objective genetic algorithm New product development

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Optimal robust linearized impulsive rendezvous

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AEROSPACE SCIENCE AND TECHNOLOGY 2007年第7-8期11卷 563-569页

作者： Tang, Guo-Jin Luo, Ya-Zhong Li, Hai-Yang Natl Univ Def Techncol Coll Aerosp & Mat Engn Changsha 410073 Peoples R China

The optimization of time-fixed linearized impulsive rendezvous with control uncertainty is investigated. One performance index related to the variances of the terminal state error is defined as the performance index of robustness which is calculated by linear covariance method. The two-objective optimization problem of minimizing the total characteristic velocity and the performance index of robustness is formulated based on the Clohessy-Wiltshire (C-W) system and solved by the nondominated sorting genetic algorithm. The Pareto-optimal solution sets of one homing rendezvous mission are provided and the Pareto optimality is verified by comparing with the fuel-optimal and the robustness-optimal solutions. It is shown that the proposed approach can quickly investigate the relation between the fuel cost and the trajectory robustness, besides evaluate different rendezvous maneuver schemes. (c) 2007 Elsevier Masson SAS. All rights reserved.

关键词： impulsive rendezvous uncertainty robust optimization multi-objective genetic algorithm

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multi-objective optimization for RNA design with multiple target secondary structures

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BMC BIOINFORMATICS 2015年第1期16卷 1-20页

作者： Taneda, Akito Hirosaki Univ Grad Sch Sci & Technol Hirosaki Aomori Japan

Background: RNAs are attractive molecules as the biological parts for synthetic biology. In particular, the ability of conformational changes, which can be encoded in designer RNAs, enables us to create multistable molecular switches that function in biological circuits. Although various algorithms for designing such RNA switches have been proposed, the previous algorithms optimize the RNA sequences against the weighted sum of objective functions, where empirical weights among objective functions are used. In addition, an RNA design algorithm for multiple pseudoknot targets is currently not available. Results: We developed a novel computational tool for automatically designing RNA sequences which fold into multiple target secondary structures. Our algorithm designs RNA sequences based on multi-objective genetic algorithm, by which we can explore the RNA sequences having good objective function values without empirical weight parameters among the objective functions. Our algorithm has great flexibility by virtue of this weight-free nature. We benchmarked our multi-target RNA design algorithm with the datasets of two, three, and four target structures and found that our algorithm shows better or comparable design performances compared with the previous algorithms, RNAdesign and Frnakenstein. In addition to the benchmarks with pseudoknot-free datasets, we benchmarked MODENA with two-target pseudoknot datasets and found that MODENA can design the RNAs which have the target pseudoknotted secondary structures whose free energies are close to the lowest free energy. Moreover, we applied our algorithm to a ribozyme-based ON-switch which takes a ribozyme-inactive secondary structure when the theophylline aptamer structure is assumed. Conclusions: Currently, MODENA is the only RNA design software which can be applied to multiple pseudoknot targets. Successful design results for the multiple targets and an RNA device indicate usefulness of our multi-objective RNA design algori

关键词： RNA switch Artificial riboswitch multi-objective genetic algorithm Pseudoknot

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