A very fast TS/SA algorithm for the job shop scheduling problem

The job shop scheduling problem (JSP) is one of the most notoriously intractable NP-complete optimization problems. Over the last 10–15 years, tabu search (TS) has emerged as an effective algorithmic approach for the JSP. However, the quality of solutions found by tabu search approach depends on the initial solution. To overcome this problem and provide a robust and efficient methodology for the JSP, the heuristics search approach combining simulated annealing (SA) and TS strategy is developed. The main principle of this approach is that SA is used to find the elite solutions inside big valley (BV) so that TS can re-intensify search from the promising solutions. This hybrid algorithm is tested on the standard benchmark sets and compared with the other approaches. The computational results show that the proposed algorithm could obtain the high-quality solutions within reasonable computing times. For example, 17 new upper bounds among the unsolved problems are found in a short time.     

模拟退火遗传算法的轮廓线拼接研究

基于断层数据的三维重构是三维数据场可视化技术的主要研究内容,重构物体的三维模型也是分析、仿真的前提.应用模拟退火遗传算法设计和实现了三维物体表面重建算法.通过在遗传算法中融人退火处理操作,提高了种群的多样性,避免了遗传算法中存在的早熟收敛问题,有效地增强了算法的全局寻优能力.此外,提出了一种基于边的最小交叉多边形算法,提高了交叉操作效率.根据轮廓线拼接问题的特点,设计了针对性强的交叉、变异操作.实验结果表明,算法有效地提高了传统的全局法轮廓线拼接算法的效率.     

基于遗传模拟退火算法的移动机器人路径规划

针对移动机器人路径规划的难题,运用了一种基于遗传模拟退火算法的移动机器人最优路径规划方法,对移动机器人的路径规划进行了设计,采用了栅格法对环境进行建模.为了提高路径规划的效率,采用了一种改进的避障算法来生成初始种群.将遗传算法与模拟退火算法相结合形成遗传模拟退火算法,新算法具有较强的全局和局部搜索能力.仿真实验结果证明算法相对于基本遗传算法的收敛速度、搜索质量和最优解输出概率方面有了明显的提高.     

基于并行组合模拟退火算法的过程挖掘

首先给出了过程挖掘问题的形式化描述,然后提出了一种适合过程挖掘的并行组合模拟退火算法。该算法采用因果关系矩阵作为过程模型的编码,与同类算法相比,对适应度函数、交叉和变异算子进行了改进,并利用模拟退火算法的特性提高了算法的收敛速度。仿真实验表明该算法能较有效地处理日志噪声问题。     

论绘画中的“视觉偏见”

当今,我们的视觉受到来自外在世界的各种影响,受到干扰后的视觉就变得不再纯粹,这使得作为视觉艺术的绘画失去了本应有的生命力。本文从视觉偏见出发来论述它产生的原因及打破视觉偏见的途径。     

模拟退火粒子群算法在新交通控制模型中的应用

城市交通系统是个随机性很强、复杂的巨型系统,为了获得良好的通行效率,提出了一种基于模拟退火温度的自适应粒子群优化算法,同时给出了一种城市区域交通协调控制信号配时模型,然后将提出的方法应用于此模型。仿真结果表明：这种算法不仅能够克服基本粒子群算法陷入局部寻优的缺点,而且算法的收敛性和稳定性都很好,同时也表明该模型是可行的、有效的。     

CAS-300光亮连续退火模拟实验机的研究与开发

介绍一台由东北大学轧制技术及连轧自动化国家重点实验室成功研制出的一种用于不锈钢冷轧后进行模拟光亮连续退火的实验机,应用德国SIEMENS公司的step7软件编程,能满足光亮连续退火实验机所要求的快速响应及控制功能。该实验设备在国内属于首创,其控制精度不低于国际先进的同类设备,文中阐述了光亮连续退火模拟实验机的特点和用途、设计功能、设备构成、人机界面、控制系统及主要性能指标。     

考虑电-氢-热多能互补的微网多目标优化配置研究

氢储能具有储能容量大、储存时间长、清洁无污染、实现多种能源网络互联互补和协同优化等诸多优点,有望成为推动分布式能源发展和提升终端能源利用效率的重要支撑技术。为了提高独立型微网供电可靠性及可再生能源利用率,本文建立了考虑电-氢-热多能互补的独立微网多目标优化配置模型,并基于模拟退火的粒子群算法对目标问题进行求解。最后,通过东北某地独立微网优化配置算例,基于MATLAB平台验证了所提多能互补配置方案较传统电储能配置方案负荷失电率降低了3.18%,可再生能源利用率提高了8.37%,所提配置方案可有效促进可再生能源消纳,保证独立微网的供电可靠性。     

Probing into Reverse Bias Dark Current in Perovskite Photodiodes: Critical Role of Surface Defects

Minimizing reverse bias dark current density (J_dark) while retaining high external quantum efficiency is crucial for promising applications of perovskite photodiodes, and it remains challenging to elucidate the ultimate origin of J_dark. It is demonstrated in this study that the surface defects induced by iodine vacancies are the main cause of J_dark in perovskite photodiodes. In a targeted way, the surface defects are thoroughly passivated through a simple treatment with butylamine hydroiodide to form ultrathin 2D perovskite on its 3D bulk. In the passivated perovskite photodiodes, J_dark as low as 3.78 × 10^-10 A cm^-2 at -0.1 V is achieved, and the photoresponse is also enhanced, especially at low light intensities. A combination of the two improvements realizes high specific detectivity up to 1.46 × 10¹² Jones in the devices. It is clarified that the trap states induced by the surface defects can not only raise the generation-recombination current density associated with the Shockley–Read–Hall mechanisms in the dark (increasing J_dark), but also provide additional carrier recombination paths under light illumination (decreasing photocurrent). The critical role of surface defects on J_dark of perovskite photodiodes suggests that making trap-free perovskite thin films, for example, by fine preparation and/or surface engineering, is a top priority for high-performance perovskite photodiodes.     

基于改进的GABP算法优化5G天线阵列

为了加快天线建模速度,针对现有天线设计软件天线参数优化速度过慢问题进行了建模研究。首先通过几种常用的启发式算法优化后的多层前馈（Back propagation,BP）神经网络对天线参数进行优化比较,并对其中最优的算法遗传算法优化BP（Genetic algorithm BP,GABP）神经网络算法进行深度改进。其次采用自适应算法和模拟退火算法优化算法对GABP进行优化。最终通过模拟试验验证出自适应GABP算法对于天线参数优化的误差最小。该研究为天线设计软件中天线优化方法提供了一种误差较小的新方法,拥有更高的预测准确度,拟合速度也大大提升。实验对比证明了该算法的可行性。