检索结果-内蒙古大学图书馆

A multi-objective genetic algorithm based approach for dynamical bus vehicles scheduling under traffic congestion

SWARM AND EVOLUTIONARY COMPUTATION 2020年 54卷 100667-000页

作者： Wang, Chunlu Shi, Hongyi Zuo, Xingquan Beijing Univ Posts & Telecommun Sch Cyberspace Secur Beijing Peoples R China Beijing Univ Posts & Telecommun Sch Comp Sci Beijing Peoples R China Minist Educ Key Lab Trustworthy Distributed Comp & Serv Beijing Peoples R China

Bus vehicle scheduling is very vital for bus companies to reduce operation cost and guarantee quality of service. Many big cities face the problem of traffic congestion, which leads to the planed vehicle scheduling scheme becoming infeasible. It is significant to study bus vehicle scheduling approaches under uncertain environments, such as traffic congestion. In this paper, a bus vehicle scheduling approach is proposed to handle the traffic congestion. It consists of three phases: firstly, a set of candidate vehicle blocks is generated once traffic congestion happens. Secondly, a non-dominated sorting genetic algorithm is adopted to select a subset of vehicle blocks from the set of candidate blocks to generate a set of Non-dominated solutions. Finally, a departure time adjustment procedure is applied to the Non-dominated solutions to further improve the quality of solutions. Experiments on a real-world bus line show that the proposed approach is able to dynamically generate scheduling schemes and significantly improve the quality of service compared to the comparative approaches.

关键词： Bus vehicle scheduling Dynamic vehicle scheduling multi-objective genetic algorithm Urban bus scheduling

来源：评论

学校读者我要写书评

暂无评论

Optimization of Aqueous Two Phase Extraction of Proteins from Litopenaeus Vannamei Waste by Response Surface Methodology Coupled multi-objective genetic algorithm

引用

CHEMICAL PRODUCT AND PROCESS MODELING 2020年第1期15卷

作者： Pandian, P. Saravana Selvan, S. Sindhanai Subathira, A. Saravanan, S. Natl Inst Technol Dept Chem Engn Tiruchirappalli 620015 Tamil Nadu India

Waste generated from industrial processing of seafood is an enormous source of commercially valuable proteins. One among the underutilized seafood waste is shrimp waste, which primarily consists of head and carapace. Litopenaeus vannamei (L. vannamei) is the widely cultivated shrimp in Asia and contributes to 90 % of aggregate shrimp production in the world. This work was focused on extraction as well as purification of value-added proteins from L. vannamei waste in a single step aqueous two phase system (ATPS). Polyethylene glycol (PEG) and trisodium citrate system were chosen for the ATPS owing to their adequate partitioning and less toxic nature. Response surface methodology (RSM) was implemented for the optimization of independent process variables such as PEG molecular weight (2000 to 6000), pH (6 to 8) and temperature (25 to 45 degrees C). The results obtained from RSM were further validated using a multi-objective genetic algorithm (MGA). At the optimized condition of PEG molecular weight 2000, pH 8 and temperature 35 degrees C, maximum partition coefficient and protein yield were found to be 2.79 and 92.37 %, respectively. Thus, L. vannamei waste was proved to be rich in proteins, which could be processed industrially through cost-effective non-polluting ATPS extraction, and RSM coupled MGA could be a potential tool for such process optimization.

关键词： Litopenaeus vannamei waste aqueous two phase system polyethylene glycol trisodium citrate response surface methodology multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

A Three-Stage Surrogate Model Assisted multi-objective genetic algorithm for Computationally Expensive Problems

A Three-Stage Surrogate Model Assisted Multi-Objective Genet...

引用

IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Jiang, Puyu Zhou, Qi Liu, Jun Cheng, Yuansheng Huazhong Univ Sci & Technol Sch Naval Architecture & Ocean Engn Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Sch Aerosp Engn Wuhan Hubei Peoples R China

ISBN: (纸本)9781728121536

multi-objective optimization problems (MOPs) are commonly encountered in practical engineering. multi-objective evolutionary algorithms (MOEAs) are one of the powerful methods to solve MOPs. However, MOEAs require a large number of fitness evaluations, which limits the practical application of MOEAs. Surrogate model assisted evolutionary algorithm (SAEA) can effectively alleviate the computation burden of MOEAs by replacing time-consuming simulation with the surrogate model. In this paper, a three-stage adaptive multi-fidelity surrogate (MFS) model assisted multi-objective genetic algorithm(MOGA) are proposed. In the first stage, a cheap low-fidelity (LF) model is adopted to obtain a preliminary Pareto frontier (PF). In the second stage, some of the individuals are selected and sent to high-fidelity (HF) model to construct MFS models, which are used to evaluate the fitness functions and sequentially updated according to the model management strategy. During this stage, in order to obtain a better PF, a fidelity control strategy is developed to subjectively determine when transforming is conducted to the third stage, in which all the individuals are evaluated by the HF model. Three benchmark tests are used to test the performance of the proposed method. Results show that the proposed method performs better than online MFS model assisted MOGA( OLMFM-MOGA) and NSGA-II with HF model, especially when the correlation between the LF and HF models is very poor.

关键词： multi-fidelity surrogate model Fidelity control strategy Surrogate model assisted evolutionary algorithm Model management multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Design of a Data-Driven Control System using a multi-objective genetic algorithm 13th

Design of a Data-Driven Control System using a Multi-Objecti...

引用

13th International-Federation-of-Automatic-Control (IFAC) Workshop on Adaptive and Learning Control Systems (ALCOS)

作者： Kinoshita, Takuya Yamamoto, Toru Hiroshima Univ 1-4-1 Kagamiyama Higashihiroshima Hiroshima Japan

In recent years, control design schemes for directly calculating control parameters from operational data have been realized and include the virtual reference feedback tuning (VRFT) method and the fictitious reference iterative tuning (FRIT) method. They were designed for objects that have a linear system. However, many objects in industry are nonlinear;hence, it is challenging to obtain good control performance by only applying fixed PID controllers. In this study, multiple linear systems as objects using multiple linear controllers are investigated. Specifically, it is necessary to solve two optimization problems of (i) the number of controllers (ii) the control parameters of each controller, and it is solving by using multi-objective genetic algorithm (MOGA) in this research. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： multi-objective genetic algorithm data-driven control VRFT

来源：评论

学校读者我要写书评

暂无评论

Optimization Design and Evaluation of Shift Point for Electric Bus Based on multi-objective genetic algorithm 3

Optimization Design and Evaluation of Shift Point for Electr...

引用

3rd Conference on Vehicle Control and Intelligence (CVCI)

作者： Lei, Yulong Zhang, Jingxu Li, Xingzhong Zhang, Yuchen Fu, Yao Jilin univ State Key Lab Automot Simulat & Control Changchun Peoples R China Jilin univ Qingdao Automobile Res Inst Changchun Peoples R China

ISBN: (纸本)9781728126845

In this paper, an integrated simulation platform of electric bus based on AVL-Cruise and MATLAB is established to provide simulation basis for optimal design of shift point. By extracting the objective function, design variables and constraint conditions, a mathematical model for solving the shift point problem with multiple objectives is established. The NSGA-II algorithm was used to carry out multi-objective optimization design for the up-stop and down-stop points to obtain the pareto optimal solution. The optimal pareto solution was evaluated and analyzed by fuzzy comprehensive evaluation method, and the optimal results of shift MAP based on three cycle conditions were obtained. This paper evaluates and analyzes the optimal results of shift MAP based on working conditions from four aspects of power performance, economy, driving performance and braking energy recovery.

关键词： electric bus mechanical automatic transmission multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of response surface method and multi-objective genetic algorithm to configuration optimization of Shell-and-tube heat exchanger with fold helical baffles

引用

APPLIED THERMAL ENGINEERING 2018年 129卷 512-520页

作者： Wang, Simin Xiao, Juan Wang, Jiarui Jian, Guanping Wen, Jian Zhang, Zaoxiao Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Shaanxi Peoples R China

A kind of shell-and-tube heat exchangers with fold baffles was proposed to eliminate the triangular leakage zones betifeen adjacent baffles. An effective algorithm combing second-order polynomial response surface method and multi-objective genetic algorithm was adopted to study the effect of fold baffle configuration parameters on the performance of flow and heat transfer. The helical angle, overlapped degree and shell-side inlet velocity were chosen as design parameters, and the Nusselt number and shell-side pressure drop were considered as objective functions. The results show that both the Nusselt number and shell-side pressure drop increase with the decrease of helical angle and shell-side inlet velocity, and increase with the increasing overlapped degree. A set of Pareto-optimal points were obtained, and the optimization results illustrate a good agreement with CFD simulation data with the relative deviation less than 3%. And the empirical correlations of Nusselt number and friction coefficient were obtained based on response surface method, the helical angle and overlapped degree were fitted into empirical correlations as correction factors for the first time. It is found that the adjusted coefficient of determination of the Nusselt number and friction coefficient is 0.943 and 0.999, respectively, which illustrate the fitting is correct and reliable. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Shell-and-tube heat exchangers Fold helical baffles Triangular leakage zones Response surface method multi-objective genetic algorithm Empirical correlation

来源：评论

学校读者我要写书评

暂无评论

Network optimisation design of Hazmat based on multi-objective genetic algorithm under the uncertain environment

引用

INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 2018年第4期12卷 236-244页

作者： Ma, Changxi Lanzhou Jiaotong Univ Sch Traff & Transportat Lanzhou 730070 Gansu Peoples R China

To avoid the hazardous material (Hazmat) transportation accidents, it is necessary to design the Hazmat transportation network in advance. Due to the uncertainty of risks and time during the Hazmat transportation, the paper studies the optimal network design method under the uncertain environment. The transportation scenario is divided into two types including single-vehicle centralised service and multi-vehicle coordinated service. The opportunity constrained programming model for the optimal design of Hazmat transportation network is constructed and the improved multi-objective genetic algorithm is used to solve the model. The case study shows the opportunity constrained programming model can better describe the optimal design of Hazmat transportation network than the traditional method under the uncertain environment. The repeating computer simulation tests show the proposed improved multi-objective genetic algorithm is feasible.

关键词： optimisation transportation network multi-objective genetic algorithm Pareto solution hazmat transportation

来源：评论

学校读者我要写书评

暂无评论

Detection and classification of cardiovascular abnormalities using FFT based multi-objective genetic algorithm

引用

BIOTECHNOLOGY & BIOTECHNOLOGICAL EQUIPMENT 2018年第1期32卷 183-193页

作者： Prasad, B. V. P. Parthasarathy, Velusamy Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala E Dept Elect & Commun Engn Madras Tamil Nadu India

Signal processing and data analysis are widely used methods in a biomedical research. In recent years, detection of cardiovascular abnormalities in patients can be achieved by using electrocardiogram (ECG) recording. In this paper, a fuzzy-based multi-objective algorithm using Fast Fourier Transform (FFT) is proposed. Initially, an effective FFT is used to extract the feature points in ECG signals, such as PQRST wave's amplitude and wave function and then the proposed multi-objective genetic algorithm is used to classify the abnormality of heart patient. Basically, the ECG behaviour depends on various factors such as age, physical condition of patients and the surrounding environment. The efficient detection of abnormalities (e.g. arrhythmia and myocardial abstraction) can be achieved by initializing the above-mentioned factors and maintaining a database containing previously attributed signals, such MIT-BIH arrhythmia. The present study provides efficiency of around 98.7% in detection of abnormalities in patients.

关键词： Fast Fourier Transform (FFT) cardiovascular abnormalities electrocardiogram (ECG) multi-objective genetic algorithm abnormalities

来源：评论

学校读者我要写书评

暂无评论

Input optimization of ANFIS typhoon inundation forecast models using a multi-objective genetic algorithm

引用

JOURNAL OF HYDRO-ENVIRONMENT RESEARCH 2018年第Mar.期19卷 16-27页

作者： Ouyang, Huei-Tau Natl Ilan Univ 1Sec 1Shennong Rd Yilan 260 Yilan County Taiwan

Inundation forecast models based on a subset of data inputs are advantageous in their efficiency due to the rather fewer inputs needed to be processed. This type of models is nevertheless rare mainly because of the difficulty in selecting the appropriate combination of input variables. In this study, an innovative methodology is proposed to overcome this difficulty by integrating Adaptive Network-based Fuzzy Inference System (ANFIS) and multi objective genetic algorithm (MOGA). The three indices of the coefficient of efficiency (CE), relative peak error (RPE) and relative time shift error (RTS) are used to assess the performances of the models from various perspectives. Optimal combinations of data inputs for the ANFIS models are searched for by MOGA, and the three models with the best performances for each index are selected. Comparisons show that the optimal models obtained by the proposed methodology have better overall performances than the ARX and Nonlinear ARX models. Test results reveal that the optimal models preferably selected for a designated prediction lead time cannot maintain optimality under different prediction leads. This problem has been resolved by the use of a series of models, each optimized with respect to a designated prediction lead time using the same methodology. Test results show that the model series exhibits significant improvements under various prediction leads and thus effectively improves the accuracy of inundation level prediction.

关键词： Optimization ANFIS Model inputs multi-objective genetic algorithm Inundation Typhoon

来源：评论

学校读者我要写书评

暂无评论

Active Control of Pressure Resonance in Long Pipeline of Bottom Founded Hydraulic Wind Turbines Based on multi-objective genetic algorithm

引用

IEEE ACCESS 2018年 6卷 53368-53380页

作者： Ai, Chao Bai, Wenjie Zhang, Tingyuan Kong, Xiangdong Yanshan Univ Minist Educ China Key Lab Adv Forging & Stamping Technol & Sci Qinhuangdao 066004 Peoples R China Yanshan Univ Hebei Heavy Machinery Fluid Power Transmiss & Con Qinhuangdao 066004 Peoples R China

The long pipeline in bottom-founded hydraulic wind turbines will greatly reduce the system natural frequency, and pressure resonances can occur more easily at multiple frequencies under time-varying wind excitation, which will reduce the electrical power quality and endanger the safe operation of the system. First, the hydraulic system impedance model is established based on electric-hydraulic analogy, and the pressure transfer function of two ends of the long pipeline is obtained, based on which the pressure resonance condition equation is solved by theoretical derivation. Furthermore, the multiple parameters sensitivity analysis of resonant frequency is carried out by using Isight and MATLAB. A novel active control strategy of pressure resonance is proposed, where the variable motor is adopted as the control object for real-time control of the terminal impedance to make the resonance frequency avoid the excitation frequency, and its feasibility is verified. Finally, with the objectives of optimizing the pressure pulsation attenuation and wind energy loss, a multi-objective genetic algorithm is used to optimize the parameters of the control object. A reliable Pareto set is obtained through multiple iterations, and different degrees of resonance suppression can be achieved.

关键词： Active control hydraulic wind turbine long pipeline multi-objective genetic algorithm pressure resonance

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：