On the Design and Optimization of a Clean and Efficient Combustion Mode for Internal Combustion Engines through a Computer NSGA-Ⅱ Algorithm

In order to address typical problems due to the huge demand of oil for consumption in traditional internal combustion engines,a new more efficient combustion mode is proposed and studied in the framework of Computational Fluid Dynamics(CFD).Moreover,a Non-dominated Sorting Genetic Algorithm(NSGA-Ⅱ)is applied to optimize the related parameters,namely,the engine methanol ratio,the fuel injection time,the initial temperature,the Exhaust Gas Re-Circulation(EGR)rate,and the initial pressure.The so-called Conventional Diesel Combustion(CDC),Homogeneous Charge Compression Ignition(HCCI)and the Reactivity Controlled Compression Ignition(RCCI)combustion modes are compared.The results show that RCCI has a higher methanol ratio and an earlier injection timing with moderate EGR rate and higher initial pressure.The initial temperature increases as the methanol ratio increases.In comparison,CDC has the lowest hydrocarbon and CO emissions and the highest combustion efficiency.At different crankshaft rotation angles corresponding to 50%of the combustion amount(CA50),the combustion temperature and boundary layer temperature of HCCI change significantly,while those of RCCI undergo limited variations.At the same CA50,the exergy losses of HCCI and RCCI are lower than that of the CDC.On the basis of these findings,it can be concluded that the methanol/diesel RCCI engine can be used to obtain a clean and efficient combustion process,which should be regarded as a promising combustion mode.

Models for Location Inventory Routing Problem of Cold Chain Logistics with NSGA-Ⅱ Algorithm

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.

多目标遗传算法NSGA-Ⅱ在某双前桥转向机构优化设计中的应用

针对东风某双前桥转向重型汽车在使用中存在的轮胎异常磨损问题,利用ADAMS/View软件建立了样车双前桥转向机构参数化仿真模型,基于选择的设计变量与目标函数,在iSIGHT软件中通过集成ADAMS/View模型,对设计变量进行了DOE分析,并利用改进的非支配排序遗传算法NSGA-Ⅱ实现了双前桥转向机构的多目标优化,根据Pareto最优解得到仿真结果表明:优化后各车轮转角误差大大减小,可有效解决车轮异常磨损问题。利用多目标遗传算法和计算机仿真集成技术对转向机构进行优化设计,可为今后汽车系统的设计、开发提供新的有效途径。

Parametric optimization of electrochemical machining of Al/15% SiC_p composites using NSGA-Ⅱ

Electrochemical machining（ECM） is one of the important non-traditional machining processes,which is used for machining of difficult-to-machine materials and intricate profiles.Being a complex process,it is very difficult to determine optimal parameters for improving cutting performance.Metal removal rate and surface roughness are the most important output parameters,which decide the cutting performance.There is no single optimal combination of cutting parameters,as their influences on the metal removal rate and the surface roughness are quite opposite.A multiple regression model was used to represent relationship between input and output variables and a multi-objective optimization method based on a non-dominated sorting genetic algorithm-Ⅱ（NSGA-Ⅱ） was used to optimize ECM process.A non-dominated solution set was obtained.

Multi-objective Function Optimization for Environmental Control of a Greenhouse Based on a RBF and NSGA-Ⅱ

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-Ⅱ could 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.

基于混合遗传蚁群算法的多目标FJSP问题研究

针对多目标柔性作业车间调度问题求解过程中未综合考虑解集多样性与求解效率的问题,提出了一种混合遗传蚁群算法来求解。首先,通过改进的NSGA-Ⅱ(non-dominated sorting genetic algorithmⅡ)获取问题的较优解,以此来确定蚁群算法的初始信息素分布;其次,根据提出的自适应伪随机比例规则和改进的信息素更新规则来优化蚂蚁的遍历过程;最后,通过邻域搜索,扩大蚂蚁的搜索空间,从而提高解集的多样性。通过Kacem和BRdata算例进行实验验证,证明混合遗传蚁群算法具有更高的求解效率和更好解集多样性。

Economic and entropy production evaluation of extractive distillation and solvent-assisted pressure-swing distillation by multi-objective optimization

Extractive distillation(ED)and solvent-assisted pressure-swing distillation(SA-PSD)are both special distillation processes that perform good at separating pressure-insensitive azeotropes.However,few reported studies have compared the performance of the two processes.In this paper,ED processes with N-methylpyrrolidone(NMP)and dimethlac-etamide(DMCA)as entrainer,SA-PSD process with isopropyl-alcohol(IPA)as solvent and SA-PSD process with partial heat integration(PHI-PSD)are proposed to achieve high purity separation of a mixture of cyclohexane/2-butanol system.The optimal operating conditions of the processes are obtained after optimizing with NSGA-Ⅱ algorithm when total annual cost(TAC)and the entropy production of process are set as objectives.The optimal results show that the optimal PHI-PSD process has lower TAC by 28.7% and the lower entropy production by 39.5% than the optimal SA-PSD process while the ED process with NMP as entrainer has lower TAC by 50.9% and the lower entropy production by 56.1% than the optimal SA-PSD process.The optimal results show that the ED process with NMP as entrainer has the best economic and thermodynamic efficiency among the four proposed processes in this paper.

铁路工程技术接口施工工序多目标协同优化研究

为解决铁路工程技术接口施工时多主体、多任务、多工序协同度不高导致的停工、资源冲突等问题,从多目标协同优化的角度对铁路工程技术接口施工工序进行研究。从系统整体的角度出发,对各个接口任务进行全方位、全过程、全要素的动态协同管理,实现分布式资源的协同与共享。利用Pareto最优原理,基于NSGA-Ⅱs算法,建立不确定环境下技术接口工期-鲁棒性-资源的多目标均衡优化模型,求得一系列Pareto最优解集,实现各个目标的协调优化。以某铁路标段桥隧连接处为例,对其技术接口进行多目标优化分析,得到23个接口工序调度方案的最优解集,并结合接口实施的实际情况,对其工期、鲁棒性和资源的需求作出优化决策,为技术接口工序工期和资源的合理安排提供参考。

基于二维离散余弦S变换的电能质量扰动类型识别

为获得可靠的高质量电能,提高电能质量扰动(Power Quality Distrubances, PQD)类型识别准确率,提出了一种基于二维离散余弦S变换(2D-DCST)的PQD类型识别方法。首先在数学模型的基础上,生成包括7种复合扰动在内的17类不同的电能质量事件。然后将一维的PQD信号转换成行列相等的二维信号,利用2D-DCST方法从二维信号中得到其振幅矩阵,对振幅矩阵提取基于统计、能量和图像的特征。再使用第二代非支配排序遗传算法(NSGA-Ⅱ)将提取的大量特征降维成少量有用的特征组。最后对所选特征使用支持向量机(SVM)分类器,构建一个分类准确率高、特征数目少的类型识别模型。实验结果表明,该方法能够准确高效地识别17类电能质量事件,并且有较好的抗噪性。同时对复合扰动也有较高的识别准确率,为电能质量扰动类型识别问题提供了新的方法。

Multi-objective capacity allocation optimization method of photovoltaic EV charging station considering V2G

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.

Dual-resource integrated scheduling method of AGV and machine in intelligent manufacturing job shop

In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in intelligent manufacturing job shop environment was studied. The dual-resource integrated scheduling model of AGV and machine was established by comprehensively considering constraints of machines, workpieces and AGVs. The bidirectional single path fixed guidance system based on topological map was determined, and the AGV transportation task model was defined. The improved A* path optimization algorithm was used to determine the optimal path, and the path conflict elimination mechanism was described. The improved NSGA-Ⅱ algorithm was used to determine the machining workpiece sequence, and the competition mechanism was introduced to allocate AGV transportation tasks. The proposed model and method were verified by a workshop production example, the results showed that the dual resource integrated scheduling strategy of AGV and machine is effective.

Multi-objective optimization design for leg mechanism of hydraulic-actuated quadruped robot

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.

Multiobjective car relocation problem in one-way carsharingsystem

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.

基于特殊正交群的工业机器人姿态插补研究

针对工业机器人因多姿态插补存在的路径不平滑、运动时间过长、速度波动率大等问题,提出了一种基于特殊正交群的机器人多姿态插补方法。首先,采用特殊正交群将获得的姿态转换为其对应的指数坐标,进而将姿态插值问题转换为对向量插值问题;其次,为保证姿态路径的连续性同时减小姿态路径的曲率对速度影响,利用三次非均匀有理B样条(NURBS)曲线和非支配排序遗传算法(NSGA-Ⅱ)以曲率L_(2)范数和长度为优化目标减小姿态路径的曲率和长度;最后,引入S形加减速对生成的姿态路径进行分段自适应加减速控制,结合弦截法和抛物线(Muller)法提出一种参数密化算法完成姿态插补。研究结果表明:与单位四元数的球面四边形插值(Squad)相比,NURBS插值的姿态路径具有C~2连续性;与标准NURBS曲线插补运动相比,优化插补运动时间缩短8.7%;与弦截法相比,所提算法的绝对平均速度波动率降低73%。

Suspended sediment load prediction using non-dominated sorting genetic algorithm Ⅱ

Awareness of suspended sediment load (SSL) and its continuous monitoring plays an important role in soil erosion studies and watershed management.Despite the common use of the conventional model of the sediment rating curve (SRC) and the methods proposed to correct it,the results of this model are still not sufficiently accurate.In this study,in order to increase the efficiency of SRC model,a multi-objective optimization approach is proposed using the Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ) algorithm.The instantaneous flow discharge and SSL data from the Ramian hydrometric station on the Ghorichay River,Iran are used as a case study.In the first part of the study,using self-organizing map (SOM),an unsupervised artificial neural network,the data were clustered and classified as two homogeneous groups as 70% and 30% for use in calibration and evaluation of SRC models,respectively.In the second part of the study,two different groups of SRC model comprised of conventional SRC models and optimized models (single and multi-objective optimization algorithms) were extracted from calibration data set and their performance was evaluated.The comparative analysis of the results revealed that the optimal SRC model achieved through NSGA-Ⅱ algorithm was superior to the SRC models in the daily SSL estimation for the data used in this study.Given that the use of the SRC model is common,the proposed model in this study can increase the efficiency of this regression model.

Multi-objective simultaneous optimal planning of electric vehiclefast charging stations and DGs in distribution system

The large-scale construction of fast charging stations(FCSs)for electric vehicles(EVs)is helpful inpromoting the EV.It creates a significant challenge for the distribution system operator to determine the optimal planning,especially the siting and sizing of FCSs in the electrical distribution system.Inappropriate planning of fast EV charging stations(EVCSs)cause a negative impact on the distribution system.This paper presented a multiobjective optimization problem to obtain the simultaneous placement and sizing of FCSs and distributed generations(DGs)with the constraints such as the number of EVs in all zones and possible number of FCSs based on the road and electrical network in the proposed system.The problem is formulated as a mixed integer non-linear problem(MINLP)to optimize the loss of EV user,network power loss(NPL),FCS development cost and improve the voltage profile of the electrical distribution system.Non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)is used for solving the MINLP.The performance of the proposed technique is evaluated by the 118-bus electrical distribution system.