Multi-Objective Optimization of VBHF in Deep Drawing Based on the Improved QO-Jaya Algorithm

Blank holder force(BHF)is a crucial parameter in deep drawing,having close relation with the forming quality of sheet metal.However,there are different BHFs maintaining the best forming effect in different stages of deep drawing.The variable blank holder force(VBHF)varying with the drawing stage can overcome this problem at an extent.The optimization of VBHF is to determine the optimal BHF in every deep drawing stage.In this paper,a new heuristic optimization algorithm named Jaya is introduced to solve the optimization efficiently.An improved“Quasi-oppositional”strategy is added to Jaya algorithm for improving population diversity.Meanwhile,an innovated stop criterion is added for better convergence.Firstly,the quality evaluation criteria for wrinkling and tearing are built.Secondly,the Kriging models are developed to approximate and quantify the relation between VBHF and forming defects under random sampling.Finally,the optimization models are established and solved by the improved QO-Jaya algorithm.A VBHF optimization example of component with complicated shape and thin wall is studied to prove the effectiveness of the improved Jaya algorithm.The optimization results are compared with that obtained by other algorithms based on the TOPSIS method.

Research Progress of Aerodynamic Multi-Objective Optimization on High-Speed Train Nose Shape

The aerodynamic optimization design of high-speed trains(HSTs)is crucial for energy conservation,environmental preservation,operational safety,and speeding up.This study aims to review the current state and progress of the aerodynamic multi-objective optimization of HSTs.First,the study explores the impact of train nose shape parameters on aerodynamic performance.The parameterization methods involved in the aerodynamic multiobjective optimization ofHSTs are summarized and classified as shape-based and disturbance-based parameterizationmethods.Meanwhile,the advantages and limitations of each parameterizationmethod,aswell as the applicable scope,are briefly discussed.In addition,the NSGA-II algorithm,particle swarm optimization algorithm,standard genetic algorithm,and other commonly used multi-objective optimization algorithms and the improvements in the field of aerodynamic optimization for HSTs are summarized.Second,this study investigates the aerodynamic multi-objective optimization technology for HSTs using the surrogate model,focusing on the Kriging surrogate models,neural network,and support vector regression.Moreover,the construction methods of surrogate models are summarized,and the influence of different sample infill criteria on the efficiency ofmulti-objective optimization is analyzed.Meanwhile,advanced aerodynamic optimization methods in the field of aircraft have been briefly introduced to guide research on the aerodynamic optimization of HSTs.Finally,based on the summary of the research progress of the aerodynamicmulti-objective optimization ofHSTs,future research directions are proposed,such as intelligent recognition technology of characteristic parameters,collaborative optimization of multiple operating environments,and sample infill criterion of the surrogate model.

Back Frame Section Size Optimization of Large Aperture Telescope

The back frame structure of a large radio telescope is an important component supporting the reflecting surface,which is directly related to the surface precision.Its optimal design is of key significance for ensuring the surface precision and reducing structural weight.Two methods are constructed to optimize the cross-section size of the telescope back frame in this paper,the criterion method and the first-order optimization method.The criterion method is based on the Lagrangian multiplier method and Kuhn-Tucker condition.This method first establishes the mathematical model by taking the inner and outer radiuses of the back frame beams as the design variables,the structural weight as the constraint condition,and the structural compliance as the objective function,then derives the optimization criterion.The first-order optimization method takes the inner and outer radiuses of the beams as the design variables,the back frame RMS as the objective function,and the structural weight as the constraint condition.Comparison of RMS,structural stress uniformity and optimization efficiency shows that both algorithms can effectively reduce structural deformation and improve RMS,but the criterion method has relatively better result than the first-order method.

CPSO: Chaotic Particle Swarm Optimization for Cluster Analysis

Background:To solve the cluster analysis better,we propose a new method based on the chaotic particle swarm optimization(CPSO)algorithm.Methods:In order to enhance the performance in clustering,we propose a novel method based on CPSO.We first evaluate the clustering performance of this model using the variance ratio criterion(VRC)as the evaluation metric.The effectiveness of the CPSO algorithm is compared with that of the traditional particle swarm optimization(PSO)algorithm.The CPSO aims to improve the VRC value while avoiding local optimal solutions.The simulated dataset is set at three levels of overlapping:non-overlapping,partial overlapping,and severe overlapping.Finally,we compare CPSO with two other methods.Results:By observing the comparative results,our proposed CPSO method performs outstandingly.In the conditions of non-overlapping,partial overlapping,and severe overlapping,our method has the best VRC values of 1683.2,620.5,and 275.6,respectively.The mean VRC values in these three cases are 1683.2,617.8,and 222.6.Conclusion:The CPSO performed better than other methods for cluster analysis problems.CPSO is effective for cluster analysis.

THEORY OF DYNAMIC OPTIMIZATION FOR MATERIALS HEATING PROCESS——CRITERION RESTRAINING METHOD

A criterion restraining mehod adopted to the dynamic optimization for materials heat- ing process has been developed,by regarding it as controlled object of a regulator in control theory and combining the optimal criterion of it.The method may be available to optimize fuel supply along furnace length and to provide a theoretical basis for the optimization of fuel supply in time-varying.For soaking pit,the calculation shows that in case of optimization by criterion restraining method,the thermal efficiency is 3.1 higher than the modelling prediction result.In comparison with heat flux-decomposing method,the thermal efficiency increased from 43.1 to 43.8%,and the energy consumption was reduced by 7.28% relative to the practical production data.

Tree Model Optimization Criterion without Using Prediction Error

The use of prediction error to optimize the number of splitting rules in a tree model does not control the probability of the emergence of splitting rules with a predictor that has no functional relationship with the target variable. To solve this problem, a new optimization method is proposed. Using this method, the probability that the predictors used in splitting rules in the optimized tree model have no functional relationships with the target variable is confined to less than 0.05. It is fairly convincing that the tree model given by the new method represents knowledge contained in the data.

Multiscale Mechanics and Optimization of Gastropod Shells

A vast majority of mollusks grow a hard shell for protection. The structure of these shells comprises several levels of hierarchy that increase their strength and their resistance to natural threats. This article focuses on nacreous shells, which are composed of two distinct layers. The outer layer is made of calcite, which is a hard but brittle material, and the inner layer is made of nacre, a tough and ductile material. The inner and outer layers are therefore made of materials with distinct structures and properties. In this article, we demonstrate that this system is optimum to defeat attacks from predators. A two-scale mod- eling and optimization approach was used. At the macroscale, a two-layer finite element model of a seashell was developed to capture shell geometry. At the microscale, a representative volume element of the microstructure of nacre was used to model the elastic modulus of nacre as well as a multiaxial failure criterion, both expressed as function of microstructural parameters. Experiments were also performed on actual shells of red abalone to validate the results obtained from simulations and gain insight into the way the shell fails under sharp perforation. Both optimization and experimental results revealed that the shell displays optimum performance when two modes of failure coincide within the structure. Finally, guidelines for designing two-layer shells were proposed to improve the performance of engineered protective systems undergoing similar structural and loading conditions.

Shape Optimization of Pressure Vessel Head Based on the Super-ellipse Equation

This paper studies optimal shape design of pressure vessel head subject to internal uniform pressure.The optimization aims at minimizing its maximum stress while the volume of the vessel head remains no less than the standard ellipsoidal head.Super-ellipse curve is selected to describe the middle surface shape of the vessel head because it represents a large family of curves with only two or three parameters and makes the design and manufacture easy.The performance of different elements and element sizes of FEM modeling is carefully studied in view of computational cost,accuracy and noises of von Mises stress.The response surface of the maximum stress vs.shape design parameters is approximated by a Kriging surrogate model with EI criterion for sampling adding,based on the parameter optimization which is carried out to search the optimal shape.Finally,it is shown by numerical comparison that the super-ellipsoidal head is better than the standard ellipsoidal head and the other vessel heads in the literature.

Optimality conditions in set optimization employing higher-order radial derivatives

There are two approaches of defining the solutions of a set-valued optimization problem： vector criterion and set criterion. This note is devoted to higher-order optimality conditions using both criteria of solutions for a constrained set-valued optimization problem in terms of higher-order radial derivatives. In the case of vector criterion, some optimality conditions are derived for isolated （weak） minimizers. With set criterion, necessary and sufficient optimality conditions are established for minimal solutions relative to lower set-order relation.

The Configuration Optimization for Multilimbed Robots with the Viewpoint of Maximum Loading Capacity

This paper presents a method for optimizing the configuration of a multilimbed robot (the robot with both arms and legs) which works with a big load. A least-effort criterion is proposed as the base of optimization. When the applying Cartesian force and the task point are given, the best configuration of the robot will be easily found through a series of imaginary motions of the robot and some simple computations. The imaginary motion varies with the working environment related to the construction of the robot, the task point and the force direction. The working environment could be predicted by the proposed inequalities, so that the way of motion could be decided in advance.

Formation mechanisms of fracture plugging zone and optimization of plugging particles

As formation mechanisms of plugging zone and criteria for fracture plugging remain unclear,plugging experiments and methods testing granular material mechanical properties are used to study the formation process of the plugging zone in fractured formations,analyze composition and ratios of different sizes of particles in the plugging zone,and reveal the essence and driving energy of the formation and damage of the plugging zone.New criteria for selecting lost circulation materials are proposed.The research results show that the formation of the plugging zone has undergone a process from inertial flow,elastic flow,to quasi-static flow.The plugging zone is composed of fracture mouth plugging particles,bridging particles and filling particles,and the proportion of the three types of particles is an important basis for designing drilling fluid loss control formula.The essence of the construction of the plugging zone is non-equilibrium Jamming phase transition.The response of the plugging zone particle system to pressure is driven by entropy force;the greater the entropy,the more stable the plugging zone.Lost circulation control formula optimized according to the new criteria has better plugging effect than the formula made according to conventional plugging rules and effectively improves the pressure-bearing capacity of the plugging zone.The research results provide a theoretical and technical basis for the lost circulation control of fractured formations.

Code Smell Detection Using Whale Optimization Algorithm

Software systems have been employed in many fields as a means to reduce human efforts;consequently,stakeholders are interested in more updates of their capabilities.Code smells arise as one of the obstacles in the software industry.They are characteristics of software source code that indicate a deeper problem in design.These smells appear not only in the design but also in software implementation.Code smells introduce bugs,affect software maintainability,and lead to higher maintenance costs.Uncovering code smells can be formulated as an optimization problem of finding the best detection rules.Although researchers have recommended different techniques to improve the accuracy of code smell detection,these methods are still unstable and need to be improved.Previous research has sought only to discover a few at a time(three or five types)and did not set rules for detecting their types.Our research improves code smell detection by applying a search-based technique;we use the Whale Optimization Algorithm as a classifier to find ideal detection rules.Applying this algorithm,the Fisher criterion is utilized as a fitness function to maximize the between-class distance over the withinclass variance.The proposed framework adopts if-then detection rules during the software development life cycle.Those rules identify the types for both medium and large projects.Experiments are conducted on five open-source software projects to discover nine smell types that mostly appear in codes.The proposed detection framework has an average of 94.24%precision and 93.4%recall.These accurate values are better than other search-based algorithms of the same field.The proposed framework improves code smell detection,which increases software quality while minimizing maintenance effort,time,and cost.Additionally,the resulting classification rules are analyzed to find the software metrics that differentiate the nine code smells.

基于代理模型估值不确定度的昂贵多目标优化问题研究

针对代理模型辅助的多目标优化算法中个体不确定度之间相互冲突的问题,本文提出个体每个目标估值不确定的填充准则,同时,为了减少训练模型消耗的计算资源,提出基于非支配排序的样本选择算法。为了验证该算法的可行性,采用DTLZ和WFG测试函数进行测试,得出结果与近些年发表5种具有代表性的同类型算法进行对比,结果说明该算法可以有效的解决昂贵高维高目标优化问题。

基于混合加点Kriging代理模型的高速列车头型气动多目标优化

在高速列车多目标气动优化设计中,结合传统加点准则建立的代理模型在初始抽样样本点较少时寻优效率较低.为提高优化效率,本文融合改善期望加点准则(EIC)及Pareto前沿解加点准则(PIC),提出混合加点准则(HIC)方法,并基于HIC方法建立Kriging代理模型,以高速列车头车气动阻力、尾车气动阻力及尾车气动升力最小为优化目标,开展高速列车头型多目标气动优化研究;并以Branin单目标测试函数和Poloni多目标测试函数为例,对比分析EIC、PIC和HIC 3种代理模型的收敛速度.结果表明:单目标优化中,相比于EIC和HIC代理模型,HIC代理模型的寻优效率提高50.0%;多目标优化中,与PIC代理模型相比,HIC代理模型的效率提高62.5%;采用HIC代理模型开展头型多目标气动优化得到的最优解模型与原始模型相比,高速列车头车气动阻力、尾车气动阻力和尾车气动升力分别降低1.6%、1.7%和3.0%;最优解模型的鼻尖高度、车钩区域高度及司机室视窗高度都有所降低,2条横向轮廓线内缩.

基于组合模型的复杂系统超多目标优化算法

代理模型辅助进化算法广泛用于昂贵的复杂工程系统优化设计,能够加速找到问题的最优解集。然而,单个模型预测性能依赖于具体问题,并且随着目标个数的增加,预测性能的不确定性将随之增加。因此,提出一种基于组合模型的复杂系统超多目标优化算法。首先,建立组合代理模型并结合随机参考向量替代机制,以更好地搜索超多目标问题的非支配解集。其次,基于改进的统计下限最小值(LCB)准则及自适应个体选择策略选择优秀个体进行真实评估,以更新组合代理模型,使其能更好地辅助算法找到最优解集。最后,通过所提算法与已有代理模型进化算法在一系列测试函数和工程优化实例上的对比结果表明,所提算法具有良好的性能和潜力。

基于优化算法量子动力学框架的势垒估计准则

量子动力学框架(QDF)是在优化算法量子动力学模型下得到的具有代表性和普遍意义的优化算法的基本迭代过程,差解接受是避免优化算法陷入局部最优、解决算法早熟问题的一种重要机制。为了在QDF中引入差解接受机制,以量子动力学模型为基础将差解视为粒子运动过程中遇到的势垒,利用量子隧道效应中的透射系数计算粒子穿透该势垒的概率,从而得到量子动力学模型下的差解接受准则:势垒估计准则(PBEC)。PBEC与势垒高度和宽度、粒子的质量均有关系,比经典的Metropolis接受准则更能全面地估计优化算法采样时遇到差解时的行为。实验结果表明,基于PBEC的QDF算法相较于基于Metropolis接受准则的QDF算法,在求解函数过程中算法跳出局部最优的能力更强、搜索效率更高,表明PBEC在量子优化算法中是一种可行且有效的差解接受机制。

基于FDS准则的响应曲面设计预测能力比较

预测能力是实际应用工作者评价设计优劣的重要准则之一,一般地,通过方差散布图可以对一个固定球面上的设计预测能力进行比较和选择,但无法获得对整个设计区域上的比较结果。文章介绍了基于正交表的响应曲面设计(OACD)以及基于极小极大准则的改进设计(OACM),并应用全区域预测方差占比准则——FDS准则对这两类中心组合设计进行预测能力的比较。结果表明,在一个较小方差范围内,OACD得到的FDS结果要优于OACM,而对于大部分给定方差值,OACM的FDS结果要优于OACD。

低雷诺数翼型多目标优化设计研究

为消除低雷诺数下对称翼型小迎角范围内的气动力非线性现象,基于高斯过程回归模型及NSGA‑Ⅱ多目标遗传算法并耦合RANS的数值方法建立了低雷诺数翼型优化设计程序,以多个状态下小迎角范围内的平均巡航因子为目标函数开展翼型优化设计。结果表明:优化翼型具有明显的几何凸起,有效改变了分离泡的位置和类型,进而显著改善翼型气动特性,Re=4×104时小迎角范围内的升力系数非线性现象基本消失。进一步分析发现优化翼型的凸起增强了壁面的对流影响和来流抵抗逆压梯度的能力,进而改善了翼型的气动特性。

基于未来降雨的水库实时优化调度研究

为了充分利用未来降雨信息指导水库调度,构建了以最大削峰为目标的水库实时调度模型,提出了一种考虑未来降雨信息的水库优化调度方法,基于水箱模型利用24 h降雨量预报信息预测入库流量并建立每个时段的泄洪指标求解模型。以山美水库防洪调度为例进行研究,与降雨启发信息优化调度方法进行比较,结果表明,此优化调度方法在目标函数上表现更好,与利用洪水预报的优化调度方法效果相近,能较好地解决来水不确定性的问题。

基于最优模型选择的多信标长基线定位系统误差辨识方法

为辨识多信标长基线定位系统误差,及提高定位精度,针对目标安装多个信标且目标体积不可忽略的情况,构建了多信标体制的长基线水下定位模型。进一步针对测元系统误差中包含的声速误差、时延误差,在多信标体制定位模型的基础上,构建了多类系统误差辨识模型,并结合水下目标定位过程,计算时延残差,构建模型最优检验统计量,给出了系统误差模型的最优选择准则,实现水下目标位置参数和系统误差参数的有效估计。仿真结果表明,该模型最优选择准则可以有效选择合适的系统误差辨识模型,提高长基线水下目标的定位精度。提出的基于最优模型选择的多信标长基线定位系统误差辨识方法可为水下目标定位试验提供理论支撑和有效参考。