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optimization of combustion, performance and emission parameters in a jatropha biodiesel engine using Non-dominatedsorting genetic algorithm-II

Sunil Dhingra,Gian Bhushan,Kashyap Kumar Dubey

《机械工程前沿（英文）》 2014年 第9卷 第1期   页码 81-94 doi: 10.1007/s11465-014-0287-9

摘要：

The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition (CI) engine using jatropha biodiesel. Response surface methodology based on Central composite design (CCD) is used to design the experiments. Mathematical models are developed for combustion parameters (Brake specific fuel consumption (BSFC) and peak cylinder pressure (Pmax)), performance parameter brake thermal efficiency (BTE) and emission parameters (CO, NOx, unburnt HC and smoke) using regression techniques. These regression equations are further utilized for simultaneous optimization of combustion (BSFC, Pmax), performance (BTE) and emission (CO, NOx, HC, smoke) parameters. As the objective is to maximize BTE and minimize BSFC, Pmax, CO, NOx, HC, smoke, a multi-objective optimization problem is formulated. Non-dominated sorting genetic algorithm-II is used in predicting the Pareto optimal sets of solution. Experiments are performed at suitable optimal solutions for predicting the combustion, performance and emission parameters to check the adequacy of the proposed model. The Pareto optimal sets of solution can be used as guidelines for the end users to select optimal combination of engine output and emission parameters depending upon their own requirements.

关键词： jatropha biodiesel     fuel properties     response surface methodology     multi-objective optimization     non-dominated sorting genetic algorithm-II    

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Optimization design of anti-seismic engineering measures for intake tower based on non-dominated sortinggenetic algorithm-II

《结构与土木工程前沿（英文）》   页码 1428-1441 doi: 10.1007/s11709-023-0998-2

摘要： High-rise intake towers in high-intensity seismic areas are prone to structural safety problems under vibration. Therefore, effective and low-cost anti-seismic engineering measures must be designed for protection. An intake tower in northwest China was considered the research object, and its natural vibration characteristics and dynamic response were first analyzed using the mode decomposition response spectrum method based on a three-dimensional finite element model. The non-dominated sorting genetic algorithm-II (NSGA-II) was adopted to optimize the anti-seismic scheme combination by comprehensively considering the dynamic tower response and variable project cost. Finally, the rationality of the original intake tower antiseismic design scheme was evaluated according to the obtained optimal solution set, and recommendations for improvement were proposed. The method adopted in this study may provide significant references for designing anti-seismic measures for high-rise structures such as intake towers located in high-intensity earthquake areas.

关键词： intake tower     NSGA-II     mode decomposition response spectrum method     anti-seismic engineering measures     optimization design     variable project cost    

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An integrated model for structure optimization and technology screening of urban wastewater systems

Yue HUANG,Xin DONG,Siyu ZENG,Jining CHEN

《环境科学与工程前沿（英文）》 2015年 第9卷 第6期   页码 1036-1048 doi: 10.1007/s11783-015-0792-z

摘要： The conventional approach to wastewater system design and planning considers each component separately and does not provide the optimum performance of the entire system. However, the growing concern for environmental protection, economic efficiency, and sustainability of urban wastewater systems requires an integrated modeling of subsystems and a synthetic evaluation of multiple objectives. In this study, a multi-objective optimization model of an integrated urban wastewater system was developed. The model encompasses subsystems, such as a sewer system, stormwater management, municipal wastewater treatment, and a wastewater reclamation system. The non-dominated sorting genetic algorithm (NSGA-II) was used to generate a range of system design possibilities to optimize conflicting environmental and economic objectives. Information from a knowledge base, which included rules for generating treatment trains as well as the performance characteristics of commonly used water pollution control measures, was utilized. The trade-off relationships between the objectives, total water pollution loads to the environment, and life cycle costs (which consist of investment as well as operation and maintenance costs), can be illustrated using Pareto charts. The developed model can be used to assist decision makers in the preliminary planning of system structure. A benchmark city was constructed to illustrate the methods of multi-objective controls, highlight cost-effective water pollution control measures, and identify the main pressures on urban water environment.

关键词： urban wastewater system     integrated modeling     multi-objective optimization     non-dominated sorting genetic algorithm (NSGA-II)    

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Multi-objective optimization of a hybrid distributed energy system using NSGA-II algorithm

Hongbo REN, Yinlong LU, Qiong WU, Xiu YANG, Aolin ZHOU

《能源前沿（英文）》 2018年 第12卷 第4期   页码 518-528 doi: 10.1007/s11708-018-0594-7

摘要：

In this paper, a multi-objective optimization model is established for the investment plan and operation management of a hybrid distributed energy system. Considering both economic and environmental benefits, the overall annual cost and emissions of CO2 equivalents are selected as the objective functions to be minimized. In addition, relevant constraints are included to guarantee that the optimized system is reliable to satisfy the energy demands. To solve the optimization model, the non-dominated sorting generic algorithm II (NSGA-II) is employed to derive a set of non-dominated Pareto solutions. The diversity of Pareto solutions is conserved by a crowding distance operator, and the best compromised Pareto solution is determined based on the fuzzy set theory. As an illustrative example, a hotel building is selected for study to verify the effectiveness of the optimization model and the solving algorithm. The results obtained from the numerical study indicate that the NSGA-II results in more diversified Pareto solutions and the fuzzy set theory picks out a better combination of device capacities with reasonable operating strategies.

关键词： multi-objective optimization     hybrid distributed energy system     non-dominated sorting generic algorithm II     fuzzy set theory     Pareto optimal solution    

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基于特定最低有效位动态阈值碳纳米管场效应晶体管的高效优化近似栅极扩散输入全加器 Research Article

Ayoub SADEGHI1,Razieh GHASEMI2,Hossein GHASEMIAN3,Nabiollah SHIRI1

《信息与电子工程前沿（英文）》 2023年 第24卷 第4期   页码 599-616 doi: 10.1631/FITEE.2200077

摘要： 采用基于非支配排序的遗传算法II，将管数和手性向量作为变量，对所提单元进行性能寻优。结果表明，在电路面积有所增加的情况下，功耗延时积性能指标提升约50%。

关键词： 碳纳米管场效应晶体管（CNTFET）；优化算法；基于非支配排序的遗传算法II（NSGA-II）；栅极扩散输入（GDI）；近似计算    

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Optimal design of steel skeletal structures using the enhanced genetic algorithm methodology

Tugrul TALASLIOGLU

《结构与土木工程前沿（英文）》 2019年 第13卷 第4期   页码 863-889 doi: 10.1007/s11709-019-0523-9

摘要： This study concerns with the design optimization of steel skeletal structures thereby utilizing both a real-life specification provisions and ready steel profiles named hot-rolled I sections. For this purpose, the enhanced genetic algorithm methodology named EGAwMP is utilized as an optimization tool. The evolutionary search mechanism of EGAwMP is constituted on the basis of generational genetic algorithm (GGA). The exploration capacity of EGAwMP is improved in a way of dividing an entire population into sub-populations and using of a radial basis neural network for dynamically adjustment of EGAwMP’s genetic operator parameters. In order to improve the exploitation capability of EGAwMP, the proposed neural network implementation is also utilized for prediction of more accurate design variables associating with a new design strategy, design codes of which are based on the provisions of LRFD_AISC V3 specification. EGAwMP is applied to determine the real-life ready steel profiles for the optimal design of skeletal structures with 105, 200, 444, and 942 members. EGAwMP accomplishes to increase the quality degrees of optimum designations Furthermore, the importance of using the real-life steel profiles and design codes is also demonstrated. Consequently, EGAwMP is suggested as a design optimization tool for the real-life steel skeletal structures.

关键词： design optimization     genetic algorithm     multiple populations     neural network    

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Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on ANN-NSGA-II

Ravindra Nath YADAV, Vinod YADAVA, G.K. SINGH

《机械工程前沿（英文）》 2013年 第8卷 第3期   页码 319-332 doi: 10.1007/s11465-013-0269-3

摘要：

The effective study of hybrid machining processes (HMPs), in terms of modeling and optimization has always been a challenge to the researchers. The combined approach of Artificial Neural Network (ANN) and Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) has attracted attention of researchers for modeling and optimization of the complex machining processes. In this paper, a hybrid machining process of Electrical Discharge Face Grinding (EDFG) and Diamond Face Grinding (DFG) named as Electrical Discharge Diamond face Grinding (EDDFG) have been studied using a hybrid methodology of ANN-NSGA-II. In this study, ANN has been used for modeling while NSGA-II is used to optimize the control parameters of the EDDFG process. For observations of input-output relations, the experiments were conducted on a self developed face grinding setup, which is attached with the ram of EDM machine. During experimentation, the wheel speed, pulse current, pulse on-time and duty factor are taken as input parameters while output parameters are material removal rate (MRR) and average surface roughness (Ra). The results have shown that the developed ANN model is capable to predict the output responses within the acceptable limit for a given set of input parameters. It has also been found that hybrid approach of ANN-NSGA-II gives a set of optimal solutions for getting appropriate value of outputs with multiple objectives.

关键词： hybrid machining processes (HMPs)     electrical discharge diamond grinding (EDDG)     artificial neural network (ANN)     genetic algorithm     modeling and optimization    

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退火-遗传算法寻优及其实现

王英

《中国工程科学》 2008年 第10卷 第7期   页码 57-59

摘要：

分析了遗传算法及退火算法的优缺点，提出用退火算法改进遗传算法局部的最优值搜索效率低问题。退火算法与遗传算法融合后，使算法在寻优结果上更加迅速精确。通过水泥的配比工程实例，与单纯的遗传算法的结果进行对比，说明该方法是有效的。

关键词： 遗传算法     退火算法     遗传算法改进    

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Outcomes of haploidentical bone marrow transplantation in patients with severe aplastic anemia-II thatprogressed from non-severe acquired aplastic anemia

《医学前沿（英文）》 2021年 第15卷 第5期   页码 718-727 doi: 10.1007/s11684-020-0807-4

摘要： Severe aplastic anemia II (SAA-II) progresses from non-severe aplastic anemia (NSAA). The unavailability of efficacious treatment has prompted the need for haploidentical bone marrow transplantation (haplo-BMT) in patients lacking a human leukocyte antigen (HLA)-matched donor. This study aimed to investigate the efficacy of haplo-BMT for patients with SAA-II. Twenty-two patients were included and followed up, and FLU/BU/CY/ATG was used as conditioning regimen. Among these patients, 21 were successfully engrafted, 19 of whom survived after haplo-BMT. Four patients experienced grade II–IV aGvHD, including two with grade III–IV aGvHD. Six patients experienced chronic GvHD, among whom four were mild and two were moderate. Twelve patients experienced infections during BMT. One was diagnosed with post-transplant lymphoproliferative disorder and one with probable EBV disease, and both recovered after rituximab infusion. Haplo-BMT achieved 3-year overall survival and disease-free survival rate of 86.4%±0.73% after a median follow-up of 42 months, indicating its effectiveness as a salvage therapy. These promising outcomes may support haplo-BMT as an alternative treatment strategy for patients with SAA-II lacking HLA-matched donors.

关键词： severe aplastic anemia     non-severe acquired aplastic anemia     haploidentical bone marrow transplantation     outcomes    

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Optimal design of steel portal frames based on genetic algorithms

CHEN Yue, HU Kai

《结构与土木工程前沿（英文）》 2008年 第2卷 第4期   页码 318-322 doi: 10.1007/s11709-008-0055-1

摘要： As for the optimal design of steel portal frames, due to both the complexity of cross selections of beams and columns and the discreteness of design variables, it is difficult to obtain satisfactory results by traditional optimization. Based on a set of constraints of the Technical Specification for Light-weighted Steel Portal Frames of China, a genetic algorithm (GA) optimization program for portal frames, written in MATLAB code, was proposed in this paper. The graph user interface (GUI) is also developed for this optimal program, so that it can be used much more conveniently. Finally, some examples illustrate the effectiveness and efficiency of the genetic-algorithm-based optimal program.

关键词： satisfactory     genetic-algorithm-based     Technical Specification     algorithm     efficiency    

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A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system usingenergy filter algorithm

Aeidapu MAHESH, Kanwarjit Singh SANDHU

《能源前沿（英文）》 2020年 第14卷 第1期   页码 139-151 doi: 10.1007/s11708-017-0484-4

摘要： In this paper, the genetic algorithm (GA) is applied to optimize a grid connected solar photovoltaic (PV)-wind-battery hybrid system using a novel energy filter algorithm. The main objective of this paper is to minimize the total cost of the hybrid system, while maintaining its reliability. Along with the reliability constraint, some of the important parameters, such as full utilization of complementary nature of PV and wind systems, fluctuations of power injected into the grid and the battery’s state of charge (SOC), have also been considered for the effective sizing of the hybrid system. A novel energy filter algorithm for smoothing the power injected into the grid has been proposed. To validate the proposed method, a detailed case study has been conducted. The results of the case study for different cases, with and without employing the energy filter algorithm, have been presented to demonstrate the effectiveness of the proposed sizing strategy.

关键词： PV-wind-battery hybrid system     size optimization     genetic algorithm    

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Hybrid genetic algorithm for bi-objective resource-constrained project scheduling

Fikri KUCUKSAYACIGIL, Gündüz ULUSOY

《工程管理前沿（英文）》 2020年 第7卷 第3期   页码 426-446 doi: 10.1007/s42524-020-0100-x

摘要： In this study, we considered a bi-objective, multi-project, multi-mode resource-constrained project scheduling problem. We adopted three objective pairs as combinations of the net present value (NPV) as a financial performance measure with one of the time-based performance measures, namely, makespan ( ), mean completion time (MCT), and mean flow time (MFT) (i.e., min /max , min /max , and min /max ). We developed a hybrid non-dominated sorting genetic algorithm II (hybrid-NSGA-II) as a solution method by introducing a backward–forward pass (BFP) procedure and an injection procedure into NSGA-II. The BFP was proposed for new population generation and post-processing. Then, an injection procedure was introduced to increase diversity. The BFP and injection procedures led to improved objective functional values. The injection procedure generated a significantly high number of non-dominated solutions, thereby resulting in great diversity. An extensive computational study was performed. Results showed that hybrid-NSGA-II surpassed NSGA-II in terms of the performance metrics hypervolume, maximum spread, and the number of non-dominated solutions. Solutions were obtained for the objective pairs using hybrid-NSGA-II and three different test problem sets with specific properties. Further analysis was performed by employing cash balance, which was another financial performance measure of practical importance. Several managerial insights and extensions for further research were presented.

关键词： backward–forward scheduling     hybrid bi-objective genetic algorithm     injection procedure     maximum cash balance     multi-objective multi-project multi-mode resource-constrained project scheduling problem    

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Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and

Mohammad Sadegh ES-HAGHI, Aydin SHISHEGARAN, Timon RABCZUK

《结构与土木工程前沿（英文）》 2020年 第14卷 第5期   页码 1110-1130 doi: 10.1007/s11709-020-0643-2

摘要： We propose a new algorithm, named Asymmetric Genetic Algorithm (AGA), for solving optimization problems of steel frames. The AGA consists of a developed penalty function, which helps to find the best generation of the population. The objective function is to minimize the weight of the whole steel structure under the constraint of ultimate loads defined for structural steel buildings by the American Institute of Steel Construction (AISC). Design variables are the cross-sectional areas of elements (beams and columns) that are selected from the sets of side-flange shape steel sections provided by the AISC. The finite element method (FEM) is utilized for analyzing the behavior of steel frames. A 15-storey three-bay steel planar frame is optimized by AGA in this study, which was previously optimized by algorithms such as Particle Swarm Optimization (PSO), Particle Swarm Optimizer with Passive Congregation (PSOPC), Particle Swarm Ant Colony Optimization (HPSACO), Imperialist Competitive Algorithm (ICA), and Charged System Search (CSS). The results of AGA such as total weight of the structure and number of analyses are compared with the results of these algorithms. AGA performs better in comparison to these algorithms with respect to total weight and number of analyses. In addition, five numerical examples are optimized by AGA, Genetic Algorithm (GA), and optimization modules of SAP2000, and the results of them are compared. The results show that AGA can decrease the time of analyses, the number of analyses, and the total weight of the structure. AGA decreases the total weight of regular and irregular steel frame about 11.1% and 26.4% in comparing with the optimized results of SAP2000, respectively.

关键词： optimization     steel frame     Asymmetric Genetic Algorithm     constraints of ultimate load     constraints of serviceability limits     penalty function    

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Improved genetic algorithm and its application to determination of critical slip surface with arbitrary

LI Liang, CHI Shichun, LIN Gao, CHENG Yungming

《结构与土木工程前沿（英文）》 2008年 第2卷 第2期   页码 145-150 doi: 10.1007/s11709-008-0016-8

摘要： In order to overcome the problem of being trapped by the local minima encountered in applying the simple genetic algorithm (GA) to search the critical slip surface of the slope, an improved procedure based on the harmony search algorithm is proposed. In the searching computation, the new solutions are obtained from the whole information of the current generation. The proposed method may be applied to calculate the minimum factors of safety of two complicated soil slopes. Comparison of the results with existing examples given by other authors has shown that the proposed method is feasible for stability analysis of soil slopes.

关键词： information     algorithm     Comparison     generation     feasible    

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Application of micro-genetic algorithm for calibration of kinetic parameters in HCCI engine combustion

HUANG Haozhong, SU Wanhua

《能源前沿（英文）》 2008年 第2卷 第1期   页码 86-92 doi: 10.1007/s11708-008-0003-8

摘要： The micro-genetic algorithm (?GA) as a highly effective optimization method, is applied to calibrate to a newly developed reduced chemical kinetic model (40 species and 62 reactions) for the homogeneous charge compression ignition (HCCI) combustion of -heptane to improve its autoignition predictions for different engine operating conditions. The seven kinetic parameters of the calibrated model are determined using a combination of the Micro-Genetic Algorithm and the SENKIN program of CHEMKIN chemical kinetics software package. Simulation results show that the autoignition predictions of the calibrated model agree better with those of the detailed chemical kinetic model (544 species and 2 446 reactions) than the original model over the range of equivalence ratios from 0.1–1.3 and temperature from 300–3 000 K. The results of this study have demonstrated that the mGA is an effective tool to facilitate the calibration of a large number of kinetic parameters in a reduced kinetic model.

关键词： homogeneous     different     combustion     autoignition     compression    

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标题 作者 时间 类型 操作

optimization of combustion, performance and emission parameters in a jatropha biodiesel engine using Non-dominatedsorting genetic algorithm-II

Sunil Dhingra,Gian Bhushan,Kashyap Kumar Dubey

期刊论文

Optimization design of anti-seismic engineering measures for intake tower based on non-dominated sortinggenetic algorithm-II

期刊论文

An integrated model for structure optimization and technology screening of urban wastewater systems

Yue HUANG,Xin DONG,Siyu ZENG,Jining CHEN

期刊论文

Multi-objective optimization of a hybrid distributed energy system using NSGA-II algorithm

Hongbo REN, Yinlong LU, Qiong WU, Xiu YANG, Aolin ZHOU

期刊论文

基于特定最低有效位动态阈值碳纳米管场效应晶体管的高效优化近似栅极扩散输入全加器

Ayoub SADEGHI1,Razieh GHASEMI2,Hossein GHASEMIAN3,Nabiollah SHIRI1

期刊论文

Optimal design of steel skeletal structures using the enhanced genetic algorithm methodology

Tugrul TALASLIOGLU

期刊论文

Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on ANN-NSGA-II

Ravindra Nath YADAV, Vinod YADAVA, G.K. SINGH

期刊论文

退火-遗传算法寻优及其实现

王英

期刊论文

Outcomes of haploidentical bone marrow transplantation in patients with severe aplastic anemia-II thatprogressed from non-severe acquired aplastic anemia

期刊论文

Optimal design of steel portal frames based on genetic algorithms

CHEN Yue, HU Kai

期刊论文

A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system usingenergy filter algorithm

Aeidapu MAHESH, Kanwarjit Singh SANDHU

期刊论文

Hybrid genetic algorithm for bi-objective resource-constrained project scheduling

Fikri KUCUKSAYACIGIL, Gündüz ULUSOY

期刊论文

Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and

Mohammad Sadegh ES-HAGHI, Aydin SHISHEGARAN, Timon RABCZUK

期刊论文

Improved genetic algorithm and its application to determination of critical slip surface with arbitrary

LI Liang, CHI Shichun, LIN Gao, CHENG Yungming

期刊论文

Application of micro-genetic algorithm for calibration of kinetic parameters in HCCI engine combustion

HUANG Haozhong, SU Wanhua

期刊论文