Continuous-time orbit problems are decidable in polynomial-time

We place the continuous-time orbit problem in P$\mathsf{P}$, sharpening the decidability result shown by Hainry [7].     

Simultaneous optimization of photostrictive actuator locations,numbers and light intensities for structural shape control using hierarchical genetic algorithm

The present paper introduces an investigation into simultaneous optimization of the PbLaZrTi-based actuator configuration and corresponding applied light intensity for morphing beam structural shapes. A finite element formulation for multiphysics analysis of coupled opto-electro-thermo-mechanical fields in PbLaZrTi ceramics is derived and verified with the theoretical solution and the commercial software ANSYS. This element is then used to simulate beam bending shape control using the orthotropic PbLaZrTi actuators and the simultaneous optimization. In this procedure, the controlling and geometrical variables are simultaneously optimized via a hierarchical genetic algorithm. A bi-coded chromosome is proposed in a hierarchical mode, which consists of some control genes (i.e. actuator location and number) and parametric genes (i.e. applied light intensity). Whether the parametric gene is activated or not is managed by the value of the first-grade control genes. The numerical results demonstrate that the achieved beam bending shapes correlate remarkably well with the expected ones and the simultaneous optimization of photostrictive actuator locations, numbers and light intensities can result in optimal actuator layout with less PbLaZrTi actuators and irradiated light energy. The simulation results also show that the hierarchical genetic algorithm has more superior performance over the conventional real-coded genetic algorithm.     

高效动态存储再分配方案与实现

为提高大小和数量都不确定的数据动态存储的空间利用率和处理速度,针对常规系统动态存储分配存在的问题,提出一种高效的动态存储再分配方案。通过减少系统动态存储分配的执行次数,在有效提高存储空间利用率的同时,提高存储空间动态分配的速度,给出动态存储再分配方案的具体实现算法,用实际数据对其性能进行测试。测试结果表明,该方案能节省36％至75％的系统存储空间,分配速度提高了20至50倍。     

基于NSGA2与FIuent耦合的分析方法翼型优化

将分析方法引入飞行器气动优化设计,在FIuent软件中进行二次开发,编写了计算熵产率的UDF,来阐述分析方法在气动优化中的作用。以二维翼型为例,通过NURBS曲线进行翼型参数化建模,将NSGA2优化算法与CFD计算耦合起来,计算低雷诺数、5°攻角下的翼型升阻比和熵产率,得到最大升阻比和最小熵产率不断调和的翼型的Pareto解。结果显示,与基准翼型相比,在升阻比提高的条件下,流场熵产率减少,能量效率提高。而且优化翼型的熵产率随着升阻比的增加而增大。     

大规模定制环境下基于产品结构复杂度的工时定额制定研究

针对大规模定制环境下产品种类多、工时制定困难的特点,为了能够快速且准确获取产品工时,研究了产品结构复杂度与工时之间的关系,提出了一种基于产品结构复杂度的工时估算方法.综合考虑影响产品结构复杂度的各种因素后,针对决策结果的排序向量决定决策者权重,引入灰色关联理论,建立了产品结构复杂度计算模型.基于数据库中的工时信息,运用MATLAB软件进行编程确定产品结构复杂度和工时之间的函数关系.最后,以某企业产品加工工时估算实例,证明了所提出的估算方法的可行性.     

基于局部复杂度的环境遮挡

为了提高基于屏幕空间的环境遮挡算法(SSAO)的渲染速度,利用局部复杂度的帧间连续性,提出一种SSAO加速算法.首先为每个像素定义局部复杂度,其中局部复杂度相似的像素会有近似的环境遮挡(AO)值;在此基础上,利用帧间相关性,对于当前帧的像素p,若能在前几帧中找到与它有近似局部复杂度的某个像素,则可以直接复用前面帧的像素的AO值而无需重新计算;最后针对AO复用过程中产生的累积误差提出一种避免误差的方法.实验结果表明,在不影响效果的情况下,该算法可以将SSAO的渲染速度提高10%~40%.     

Coordinate descent with arbitrary sampling I: algorithms and complexity†

We study the problem of minimizing the sum of a smooth convex function and a convex block-separable regularizer and propose a new randomized coordinate descent method, which we call ALPHA. Our method at every iteration updates a random subset of coordinates, following an arbitrary distribution. No coordinate descent methods capable to handle an arbitrary sampling have been studied in the literature before for this problem. ALPHA is a very flexible algorithm: in special cases, it reduces to deterministic and randomized methods such as gradient descent, coordinate descent, parallel coordinate descent and distributed coordinate descent—both in nonaccelerated and accelerated variants. The variants with arbitrary (or importance) sampling are new. We provide a complexity analysis of ALPHA, from which we deduce as a direct corollary complexity bounds for its many variants, all matching or improving best known bounds.     

Safe Autonomous Agent Formation Operations Via Obstacle Collision Avoidance

In this paper, we consider the problem of flocking and shape‐orientation control of multi‐agent systems with inter‐agent and obstacle collision avoidance. We first consider the problem of forcing a set of autonomous agents to form a desired formation shape and orientation while avoiding inter‐agent collision and collision with convex obstacles, and following a trajectory known to only one of the agents, namely the leader of the formation. Then we build upon the solution given to this problem and solve the problem of guaranteeing obstacle collision avoidance by changing the size and the orientation of the formation. Changing the size and the orientation of the formation is helpful when the agents want to go through a narrow passage while the existing size or orientation of the formation does not allow this. We also propose collision avoidance algorithms that temporarily change the shape of the formation to avoid collision with stationary or moving nonconvex obstacles. Simulation results are presented to show the performance of the proposed control laws.     

A note about the complexity of minimizing Nesterov's smooth Chebyshev–Rosenbrock function

This short note considers and resolves the apparent contradiction between known worst-case complexity results for first- and second-order methods for solving unconstrained smooth nonconvex optimization problems and a recent note by Jarre [On Nesterov's smooth Chebyshev–Rosenbrock function, Optim. Methods Softw. (2011)] implying a very large lower bound on the number of iterations required to reach the solution's neighbourhood for a specific problem with variable dimension.