A Constraint-Based Approach for Deriving 3-D Structures of Cyclic Polypeptides

This paper presents an hybrid algorithm for deriving 3-D structures of cyclic polypeptides. The algorithm combines constraint-based techniques with the most widely used methods for non-cyclic polypeptides. The empirical results demonstrate that the proposed hybrid algorithm outperforms traditional methods especially with respect to running times.     

A new neural network algorithm for planarization problems

To deal with the planarization problem widely used in many applications including routing very-large-scale integration （VLSI） circuits, this paper points out that only when its vertices are arranged in some specific order in a line can a planar graph be embedded on a line without any cross connections or cross edges. Energy function is proposed to meet the need of embedding a graph on a single line and route it correctly. A Hopfield network is designed according to the proposed energy function for such embedding and routing. The advantage of the proposed method is that it not only can detect if a graph is a planar one or not, but also can embed a planar graph or the maximal planar subgraph of a non-planar graph on a single line. In addition, simulated annealing is employed for helping the network to escape from local minima during the running of the Hopfield network. Experiments of the proposed method and its comparison with some existent conventional methods were performed and the results indicate that the proposed method is of great feasibility and effectiveness especially for the planarization problem of large graphs.     

A Review of the Application of Meta-Heuristic Algorithms to 2D Strip Packing Problems

This paper is a review of the approachesdeveloped to solve 2D packing problems withmeta-heuristic algorithms. As packing tasks arecombinatorial problems with very large searchspaces, the recent literature encourages theuse of meta-heuristic search methods, inparticular genetic algorithms. The objective ofthis paper is to present and categorise thesolution approaches in the literature for 2Dregular and irregular strip packing problems.The focus is hereby on the analysis of themethods involving genetic algorithms. Anoverview of the methods applying othermeta-heuristic algorithms including simulatedannealing, tabu search, and artificial neuralnetworks is also given.     

供应链集成化模型与优化

本文建立了一个包括供应商、制造商、销售商 在内的集成化模型,这一模型含有线性状态方程和神经网络非线性模型,提出了库存成本、 供应成本、生产水平等在内的供应链目标函数和约束条件．对于供应链集成化模型采用模拟 退火方法进行优化,并以辽化公司为背景进行了初步条件的仿真工作．     

异步轧制对二次再结晶取向硅钢磁性能的影响

研究了异步轧制条件下不同厚度的二次再结晶取向硅钢成品的磁性能的变化,找到了硅钢磁性能与成品厚度和异步速比之间的关系.     

Effect of Hot Band Annealing on Magnetic Properties in 3% Si Grain‐oriented Electrical Steels

Hot band annealing is known to be a prerequisite for good magnetic properties irrespective of manufacturing methods in grain‐oriented Fe‐3 wt.% Si electrical steels. In this study, the effects of hot band annealing on magnetic properties were investigated in 3% grain‐oriented electrical steels of low soluble AI contents and one‐stage cold rolling. Microstructure and precipitate distribution were compared with hot band annealing conditions. Secondary recrystallization behaviour with hot band annealing condition was also discussed.     

Robust Estimation of Rotation Angles from Image Sequences Using the Annealing M-Estimator

A robust method is presented for computing rotation angles of image sequences from a set of corresponding points containing outliers. Assuming known rotation axis, a least-squares (LS) solution are derived to compute the rotation angle from a clean data set of point correspondences. Since clean data is not guaranteed, we introduce a robust solution, based on the M-estimator, to deal with outliers. Then we present an enhanced robust algorithm, called the annealing M-estimator (AM-estimator), for reliable robust estimation. The AM-estimator has several attractive advantages over the traditional M-estimator: By definition, the AM-estimator involves neither scale estimator nor free parameters and hence avoids instabilities therein. Algorithmically, it uses a deterministic annealing technique to approximate the global solution regardless of the initialization. Experimental results are presented to compare the performance of the LS, M- and AM-estimators for the angle estimation. Experiments show that in the presence of outliers, the M-estimator outperforms the LS estimator and the AM-estimator outperforms the M-estimator.     

基于一类SM SA 策略的模型最优降阶

将一类SMSA混合策略应用于模型的最优降阶，提出了处理约束优化和解决模型降阶通常遇到的稳定性问题的有效方法．通过对典型例子的数值仿真表明了混合策略和约束处理方法的有效性，而且第3个例子的优化结果明显优于以往文献的结果。     

Gd5(Ge2-xSi2-xM2x)化合物的晶体结构和磁性研究

研究了用稳定元素Mn、Mo、Al和V代替非磁性的Si和Ge对Gd5Ge2Si2化合物的居里温度的影响；并且研究了Gd5(Ge2-xSi2-xM2x)(M=Mn、Mo、Al和V)样品退火处理对居里温度的影响．结果表明少量的合金化元素替代会提高Gd5Ge2Si2化合物的居里温度；退火后居里温度随替代元素的含量变化比退火前更敏感．X射线粉末衍射分析表明少量的合金化元素(Mn、Mo、Al和V)替代不会影响母体Gd5Ge2Si2化合物的晶体结构．对样品的晶态显微组织和表面微结构研究发现退火后组织分布比退火前更均匀。     

基于遗传模拟退火算法的矩形件排样

将遗传模拟退火算法运用在矩形件排样中,利用遗传模拟退火算法的全局搜索能力,寻找出排样件最优的排样次序(排列最紧密),再结合基于局部板材利用率最高的填充算法不断填充板材,获得近似总体最优的排样结果。此结果适合应用于大批量、多种类的矩形件优化样。