基于时间片段的多IT项目人力资源调度问题求解

针对多个IT项目的人力资源调度问题, 根据其在时间和人员方面的特殊要求, 可以将项目的演进时间划分 为相等的时间片段, 然后根据特定时间片段内的活动与可选人员之间的关系, 建立相应的人员调度方案搜索树. 将所有时间片段内的搜索树按顺序连接后, 可以得到总的方案树, 并列出所有的方案, 然后根据不同方案下得到的平均提前完工率和提前完工率方差, 找到最优解. 又为该搜索算法添加了启发规则, 使搜索空间急剧收缩, 极大提高了搜索效率. 基于该算法的特殊性, 可以将其用于求解许多具有与上述问题类似条件的资源调度问题. 本研究通过实例发现, 根据运算中的特殊规律, 该算法还具有进一步提取启发规则的潜力.     

基于威胁特征点的启发式航迹规划方法

针对现有启发式航迹规划方法在决策变量、启发函数的选取和航迹表示方法等方面存在的不足,提出了一种基于威胁特征点的航迹规划新方法。该方法以导弹运动姿态角作为决策变量,通过引入特征点构造新的启发函数,以导弹经过空间的威胁度累积值、需用过载等为代价,结合导弹性能约束,采用龙格-库塔(Runge Kutta, R-K)积分得到平滑航迹。最后,以倾斜转弯面对称远程超音速导弹为例,通过攻防仿真实验,证明该方法规划生成的航迹满足各种约束条件且具有较高突防概率。     

Improved ant colony optimization algorithm for the traveling salesman problems

Ant colony optimization (ACO) is a new heuristic algorithm which has been proven a successful technique and applied to a number of combinatorial optimization problems.The traveling salesman problem (TSP) is among the most important combinatorial problems.An ACO algorithm based on scout characteristic is proposed for solving the stagnation behavior and premature convergence problem of the basic ACO algorithm on TSP.The main idea is to partition artificial ants into two groups: scout ants and common ants.The common ants work according to the search manner of basic ant colony algorithm,but scout ants have some differences from common ants,they calculate each route's mutation probability of the current optimal solution using path evaluation model and search around the optimal solution according to the mutation probability.Simulation on TSP shows that the improved algorithm has high efficiency and robustness.     

Analyses of location-price game on networks with stochastic customer behavior and its heuristic algorithm

<正> In this paper,a two-stage model is developed to investigate the location strategy andthe commodity pricing strategy for a retail firm that wants to enter a spatial market with multiplecompetitive facilities,where a competitor firm is already operating as a monopoly with several outlets.Expected market shares are calculated based on the stochastic customer behavior on networks.Theauthors provide a sufficient condition for the existence of equilibrium prices in the price game for thefirst time.The existence and uniqueness of the pure strategy Nash equilibrium price with a specifiedutility function are proved in the subgame.A metaheuristic based on tabu search is proposed tosearch the optimal location-price solution of the model.In addition,the authors provide two numericalexamples to illustrate how to obtain the optimal solution and conduct sensitivity analysis.The analysisshows that the best location decision is robust for the follower firm,price game is more intense whenincomes of consumers are lower or there are more substitution products,and neither chain retail gainsfrom the price competition.     

基于PS-Level Set的嘴唇几何形状定位模型

针对面向唇读的水平集模型在嘴唇分割中存在边界过收敛和过早收敛的问题,文中提出了一种改进的基于先验知识的水平集模型(简称为PS-Level Set)来进行嘴唇几何形状的定位.PS-Level Set模型利用改进的差值能量函数引入嘴唇形状的先验信息.在曲线演化过程中,反复比较演化曲线和先验曲线的差距,使曲线的演化形状逐渐逼近先验模型形状,从而更精确地收敛于目标物体实际轮廓.实验表明,用PS-Level Set模型定位嘴唇几何形状的准确率比用水平集模型提高了8.38%.     

"程度副词+名词"与潜语言的显性化

从修辞学的角度来说,“程度副词＋名词”这一结构是一种由潜在语言现象变成显性语言的现象,主要体现在以上下三个方面：潜词义的显性化;潜在功能的显性化;潜性效果的显性化。     

Covariance/Invariance: A Cognitive Heuristic in Einstein's Relativity Theory Formation

Relativity Theory by Albert Einstein has been so far littleconsidered by cognitive scientists, notwithstanding its undisputedscientific and philosophical moment. Unfortunately, we don't have adiary or notebook as cognitively useful as Faraday's. But physicshistorians and philosophers have done a great job that is relevant bothfor the study of the scientist's reasoning and the philosophy ofscience. I will try here to highlight the fertility of a `triangulation'using cognitive psychology, history of science and philosophy of sciencein starting answering a clearly very complex question:why did Einstein discover Relativity Theory? Here we arenot much concerned with the unending question of precisely whatEinstein discovered, that still remains unanswered, for we have noconsensus over the exact nature of the theory's foundations(Norton 1993). We are mainly interested in starting to answer the`how question', and especially the following sub-question: what(presumably) were his goals and strategies in hissearch? I will base my argument on fundamental publications ofEinstein, aiming at pointing out a theory-specific heuristic, settingboth a goal and a strategy: covariance/invariance.The result has significance in theory formation in science, especiallyin concept and model building. It also raises other questions that gobeyond the aim of this paper: why was he so confident in suchheuristic? Why didn't many other scientists use it? Where did he keep ? such a heuristic? Do we have any other examples ofsimilar heuristic search in other scientific problemsolving?     

两相连续铸钢周期Stefan问题解的渐近性质

本文研究了潜热Ｌ→Ｌ０〉０时，两相连续铸钢周期Ｓｔｅｆａｎ总理解｛ｕＬ（ｘ，ｔ），ｓＬ（ｔ）｝的渐近性质，并给出误差估计。     

蜗壳座环结构选型优化

提出了最佳结构型式概念；证明了最佳型式的存在性问题；建立了启发式算法．实例计算证明，选型优化不仅巧妙地融合了形状、拓朴、布局优化理论与方法的优点，而且简单可靠．     

矩形物体布局的并行算法

分析了矩形物体布局串行算法的计算复杂性，设计出基于ＳＩＭＤ－ＣＲＥＷ共享存储模型的矩形物体布局的并行算法，通过比较和实例分析验证了该并行算法的有效性和快速求解能力。