An improved differential evolution algorithm for vehicle routing problem with simultaneous pickups and deliveries and time windows

The vehicle routing problem with simultaneous pickups and deliveries and time windows (VRP-SPDTW) is the problem of optimally integrating forward (good distribution) and reverse logistics (returning materials) for cost saving and environmental protection. We constructed a general mixed integer programming model of VRP-SPDTW. The model contained some classical vehicle routing problems as special cases. We proposed an improved differential evolution algorithm (IDE) for solving this problem. In the algorithm, we firstly adopted the novel decimal coding to construct an initial population, then used some improved differential evolution operators unlike the existing algorithm, and in mutation operation, we used an integer order criterion based on natural number coding method. We introduced a penalty technical to publish the infeasible solution. In addition, in the crossover operation, we designed a self-adapting crossover probability that varied with iteration. We did some numerical experiments, and the results showed that the proposed method is effective for solving VRP-SPDTW.     

PSO-based single multiplicative neuron model for time series prediction

Single multiplicative neuron model is a novel neural network model introduced recently, which has been used for time series prediction and function approximation. The model is based on a polynomial architecture that is the product of linear functions in different dimensions of the space. Particle swarm optimization (PSO), a global optimization method, is proposed to train the single neuron model in this paper. An improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. The proposed CRPSO, PSO, back-propagation algorithm and genetic algorithm are employed to train the model for three well-known time series prediction problems. The experimental results demonstrate the superiority of CRPSO-based neuron model in efficiency and robustness over the other three algorithms.     

The influence of grain geometry and wear conditions on the material removal mechanism in silicon carbide grinding with single grain

High efficiency and precision grinding of brittle materials is challenging due to material physical and chemical properties. To understand the effect of grain geometry and wear conditions on the material removal mechanism in brittle material precision grinding, a single diamond grain grinding experiment was conducted on Silicon Carbide (SiC). The cutting edge radius and deflection angle were measured by confocal scanning. Under six different cutting edge radius and three maximum undeformed chip thickness, grinding force and ground surface were measured. Diamond grain wear was investigated by observing the grain morphology, wear rate, grinding force, and ground surface change over accumulative material removal volume. The result showed the existence of a critical cutting edge radius for improving SiC ground surface quality.. Normal grinding force increased with the cutting edge radius increase. Tangential grinding force increased with the cutting edge radius increase and reached the peak value at the critical cutting edge radius. Flank wear was the major wear mode in precision SiC grinding. The grain wear was associated with the grinding force and ground surface.     

Optimal mean-square N-observation digital morphological filters: I. Optimal binary filters

The present paper places binary morphological filtering into the framework of statistical estimation, the intent being to develop the theory of mean-square (MS) optimization. Classical binary morphological operations are interpreted as numerical functionals on binary N-vectors, so that in the random setting they can be treated as estimators dependent on N binary observation random variables. For single-erosion filters, optimization is achieved by finding the structuring element that minimizes MS error. Using the Matheron representation as a guide, we generalize the analysis to morphological filters given by unions of multiple erosions and optimize by minimizing MS error over all collections of erosions, or over a prefixed number of erosions. In all cases, MS error is relative to the estimation of an unobserved variable by a morphological function of observed variables. A key element in the method is use of the basis form of the Matheron expansion to reduce significantly the structuring-element search. The technique is adapted to special morphological filters by constraining the basis representation in accordance with the class of interest. It is demonstrated that optimization in terms of erosions is equivalent to optimization in terms of dilations.     

Development and performance of a magnetic ionic liquid for use in vacuum-compatible non-contact seals

For the electron-beam machining of optical media, a very low rotational speed is required to enable the precise fabrication of grooves of various depths and widths. In addition, a lubricant with a very low vapour pressure, such as an ionic liquid, and a vacuum chamber are needed to avoid contamination of workpieces. Accordingly, the development of a vacuum-compatible hydrostatic bearing using an ionic liquid is required to satisfy these rotational conditions and nanometre-order machining accuracy. To use a hydrostatic bearing in a vacuum environment, a non-contact vacuum seal is needed to avoid leakage of the ionic liquid used as the lubricant. Furthermore, making a non-contact seal using an ionic liquid requires the development of a new type of magnetic ionic liquid. Therefore, this paper describes the development of such a magnetic ionic liquid, which consists of magnetite (Fe₃O₄) particles, a newly synthesized dispersant, and a pyridinium-based ionic liquid. The outgassed products from this magnetic ionic liquid were measured when it was applied to a non-contact seal in a vacuum of about 10⁻⁶ Pa. In addition, its mechanical properties, such as viscosity and burst pressure as a non-contact seal, were measured. From these investigations, it was found that the developed magnetic ionic liquid would meet the requirements for non-contact seals to be used in vacuum-compatible hydrostatic bearings.     

Applying evolutionary prototyping model for eliciting system requirement of meat traceability at agribusiness level

Traceability has become an effective method of ensuring food safety and connecting stakeholders in the food chain. There is an increasing growth trend in developing IT-based traceability system in recent years. But implementing hastily traceability system is likely to fail to achieve its goal if the system requirement has not been well-defined according to the changing business environment. This paper adopted an evolutionary prototyping model and used longitudinal case study to elicit the traceability system requirement at the level of agribusiness. The results show that a traceability system can support not only information tracking at operational level, but also diagnostic analysis and strategic decision making at managerial level, Hence, system requirements can be categorized as fundamental, decisive and strategic levels. The evolutionary prototyping model can improve the effectiveness of requirement elicitation.     

平板式半挂车车架有限元分析

应用Pro／E对平板式半挂车车架进行三维实体建模。对该模型进行简化处理、抽中面和修补后导入ANSYS。采用壳单元建立平板式半挂车车架的有限元模型,对车架进行静力分析和模态分析。结果表明,车架在弯曲和扭转工况下,刚度和强度满足要求;车架结构的低阶模态频率不在路面激励频带之内,不会产生共振现象。     

Modelling of turbulent wind flow using the embedded Markov chain method

Small wind turbines are usually installed to provide off-grid power and as such can be situated close to the load in a less-than-ideal wind resource. These wind regimes are often governed by low mean speeds and high wind turbulence. This can result in energy production less than that specified by the manufacturer's power curve. Wind turbulence is detrimental to the fatigue life of key components and overall turbine reliability and therefore must be considered in the design stage of small wind turbines. Consequently it is important to accurately simulate wind speed data at highly turbulent sites to quantify loading on turbine components. Here we simulate wind speed data using the Markov chain Monte Carlo process and incorporate long term effects using an embedded Markov chain. First, second and third order Markov chain predictions were found to be in good agreement with measured wind data acquired at 1 Hz. The embedded Markov chain was able to predict site turbulent intensity with a reasonable degree of accuracy. The site exhibited distinctive peaks in wind speed possibly caused by diurnal heating and cooling of the earth's surface. The embedded Markov chain method was able to simulate these peaks albeit with a time offset.     

基于多源信号的单向阀内泄漏预测研究

单向阀作为液压系统重要元件,发生内泄漏故障时影响液压系统的工作效率和设备的安全稳定运行。针对单向阀内泄漏预测,提出了一种基于多源信号和布谷鸟搜索支持向量回归(CS-SVR)的单向阀内泄漏无损预测方法。首先建立单向阀内泄漏检测实验平台,获得不同工况不同故障特征下单向阀内泄漏的振动信号和声发射信号。然后利用小波包能量分析方法,提取两种信号最优频带重构信号的均方根值作为预测变量,并结合阀前压力建立基于布谷鸟算法优化的支持向量机回归(CS-SVR)的多源信号预测模型。最后,将模型进行对比分析。结果表明,布谷鸟搜索算法相对于网格搜索法(GS)和粒子群算法(PSO)对SVR模型参数寻优优势更大;基于多源信号输入的预测方法相对于单源输入的预测方法精确程度更高,同时该方法能实现不同压力、不同故障类别、不同故障程度的单向阀内泄率预测,平均相对误差为8.97%鲁棒性较高,为阀内泄漏无损检测应用技术的开发奠定了基础。     

Influence of micropolar lubricants on the performance of slot-entry hybrid journal bearing

A theoretical study concerning the slot-entry hybrid journal bearing lubricated with micropolar lubricants is presented. The modified Reynolds equation for micropolar lubricant is solved using finite element method along with equation of lubricant flow through slot-entry restrictors as a constraint together with appropriate boundary conditions. It has been observed that a slot-entry hybrid journal bearing operating with micropolar lubricant shows an increase in the value of minimum fluid film thickness and a reduction in the value of coefficient of friction as compared to a corresponding similar slot-entry hybrid journal bearing operating with Newtonian lubricant.