基于改进人工蜂群算法的多目标绿色柔性作业车间调度研究

针对多目标绿色柔性作业车间调度问题（MGFJSP）的特点，提出从碳排放量、噪声和废弃物这3个指标来综合评定环境污染程度，建立了以最小化最大完成时间和环境污染程度为优化目标的MGFJSP模型，并提出了一种改进的人工蜂群算法来求解该模型。算法的具体改进包括：设计了一种三维向量的编码和对应解码方案，在跟随蜂搜索阶段引入一种有效的动态邻域搜索操作来提高算法的局部搜索能力，在侦查蜂阶段提出产生新食物源的策略用于增加种群的多样性。最后进行了实验研究与算法对比，以验证所建模型和所提算法的有效性。     

Multilevel adaptive control of nonlinear interconnected systems

This paper presents an adaptive backstepping-based multilevel approach for the first time to control nonlinear interconnected systems with unknown parameters. The system consists of a nonlinear controller at the first level to neutralize the interaction terms, and some adaptive controllers at the second level, in which the gains are optimally tuned using genetic algorithm. The presented scheme can be used in systems with strong couplings where completely ignoring the interactions leads to problems in performance or stability. In order to test the suitability of the method, two case studies are provided: the uncertain double and triple coupled inverted pendulums connected by springs with unknown parameters. The simulation results show that the method is capable of controlling the system effectively, in both regulation and tracking tasks.     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

A multi-start central force optimization for global optimization

Central force optimization (CFO) is an efficient and powerful population-based intelligence algorithm for optimization problems. CFO is deterministic in nature, unlike the most widely used metaheuristics. CFO, however, is not completely free from the problems of premature convergence. One way to overcome local optimality is to utilize the multi-start strategy. By combining the respective advantages of CFO and the multi-start strategy, a multi-start central force optimization (MCFO) algorithm is proposed in this paper. The performance of the MCFO approach is evaluated on a comprehensive set of benchmark functions. The experimental results demonstrate that MCFO not only saves the computational cost, but also performs better than some state-of-the-art CFO algorithms. MCFO is also compared with representative evolutionary algorithms. The results show that MCFO is highly competitive, achieving promising performance.     

Design for comfort and social interaction in future vehicles: A study on the leg space between facing-seats configuration

With the advent of future vehicles, passengers expect to travel in comfort, and the free leg space between facing-seats could be an issue due to the unsuitability for all people, according to their anthropometric variability. A previous investigation survey showed the need to increase the leg-space between facing seats and, if installed, to improve the surface of the table placed in between. So, four different distances between seat-pans front edges of facing seats have been set-up and tested (44 cm, 51 cm, 58 cm, 65 cm) with a table in between. 13 couples of participants with different heights took part to experiments. The aim was to investigate the relationship between facing-seat distances and passenger wellbeing in terms of postural comfort and social interaction. Postural comfort has been analysed through optical tracking (for postural angles overtime) and questionnaires (perceived comfort). Social interaction feelings have been investigated with questionnaires. Experiment results showed the suitable distance could be 51 cm keeping the same table surface; otherwise, the 65 cm one could be ideal changing the table surface.Relevance to industryWith the advent of autonomous driving, vehicle manufacturers and designers are working hard to define new paradigms of public transportation in terms of seat layout, passenger wellbeing and interiors’ design. This paper contributes to increasing the general knowledge on the effects of distance between facing seats on postural comfort and social interaction.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

一种军棋机器博弈的多棋子协同博弈方法

针对在军棋博弈不完全信息对弈中，面对棋子不同价值、不同位置、不同搭配所产生的不同棋力，传统的单子意图搜索算法，不能满足棋子之间的协同性与沟通性，同时也缺乏对敌方的引诱与欺骗等高级对抗能力。本文提出一种结合UCT搜索策略的高价值棋子博弈方法，实现高价值棋子协同博弈的策略。实战经验表明:高价值多棋子军棋协同博弈策略优于单棋子军棋博弈策略。     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

基于ＰＩＤ控制算法的直流微网容错控制方法研究

构建直流微网容错控制对象模型，调节直流微电网的输出回路参数；以输出功率、直流微网的 参考电压、弱电网下系统惯性响应特征等为约束参量，构建直流微网容错控制目标函数，在不同电网强度下 进行直流微网容错控制的参数自整定性调节，采用无功环比例积分控制方法进行直流微网容错寻优分析， 建立模糊 ＰＩＤ控制模型，采用变结构的模糊 ＰＩＤ控制方法进行直流微网容错控制过程中的自适应加权学习 和误差反馈调节，实现直流微网容错控制改进设计。仿真结果表明，采用该方法进行直流微网控制的容错 性能较好，输出稳定性较强，具有较好的直流微网输出增益。     

基于改进NSGA-Ⅱ算法的乙烯裂解炉操作优化

现有的乙烯裂解炉优化通常只针对两个目标函数即产物乙烯和丙烯的收率，并且采用遗传算法的收敛效果一般，故提出一种基于改进NSGA-Ⅱ算法来研究一个多目标运行的解决方案，以此来解决乙烯裂解炉的固定周期操作优化问题，即在增大产物乙烯和丙烯收率的同时减少原料以及蒸汽流量来提高整体运行状况。把具体问题量化为数学模型，分析了原料气烃比、原料流量、出口温度对乙烯和丙烯收率的影响。实验结果表明，相较于原有操作条件，提出的优化方案具有良好的可行性。