小波变换在求解重力测定反问题中的应用

针对重力测定反问题,提出将其离散为线性不适定问题,利用小波变换方法进行数值求解.该方法将小波变换和正则化方法相结合,选取小波函数作为一组基底,将原不适定问题转化为粗子空间上的适定问题,并给出选取粗子空间基的方法.通过数值模拟已有方法和小波变换方法求解结果的比较,表明了小波变换方法的可行性和有效性.     

职业教育书写“中国梦”的路径选择

近年来,我国职业教育取得了空前的发展和进步,但是不可否认,职业教育仍然存在许多问题,如何解决这些问题,需要分析实际情况,从宏观、中观、微观、规范、外因、内因等方面解决现实问题。     

本科生导师制激励问题研究

运用博弈论的分析方法解释本科生导师制在推行过程中遇到的激励问题。通过构建一个非对称信息的静态模型,发现导师指导学生的努力程度将取决于学校的惩罚力度、考核成本以及该制度给学校带来的收益,而学校对教师指导情况的考核概率则主要受到其制定的奖惩规则和教师科研水平的影响。     

Sampling average approximation method for a class of stochastic Nash equilibrium problems

We consider a class of stochastic Nash equilibrium problems (SNEP). Under some mild conditions, we reformulate the SNEP as a stochastic mixed complementarity problem (SMCP). We apply the well-known sample average approximation (SAA) method to solve the SMCP. We further introduce a semismooth Newton method to solve the SAA problems. The comprehensive convergence analysis is given as well. In addition, we demonstrate the proposed approach on a stochastic Nash equilibrium model in the wholesale gas–oil markets.     

改进的猴王遗传算法求解组合拍卖最优竞胜标

应用遗传算法求解第一价格封闭组合拍卖问题,编码及约束条件复杂,在交叉和变异的过程中容易产生大量不可行解,并且在选择和精英保留中,一些局部最优点(早熟点)对应的个体容易被大量复制,使群体多样性下降。该文就以上的问题,改进了原有遗传算法求解组合拍卖最优竞胜标的方法,并采用了猴王遗传算法的精英保留策略。实际计算证明本算法编码方式自然并且直观表达了个体和标的的关系。在交叉和变异算子中,产生不可行解的数量下降,更积极的保存了上一代进化的部分成果。而改进猴王遗传算法的精英保留策略,使算法能够以高概率跳出早熟,达到算法速度与准确的平衡。     

A method for numerical solution of a multidimensional convection-diffusion problem

We propose a modification of the additive splitting algorithm to solve the convection-diffusion problem using an efficient finite-difference scheme. The modification decreases the number of data exchanges and their amount during the numerical solution of a system of multidimensional equations. Approximation, stability, and convergence are considered. Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 100–107, January–February 2009.     

The method of fundamental solutions for problems in static thermo-elasticity with incomplete boundary data

An inverse problem in static thermo-elasticity is investigated. The aim is to reconstruct the unspecified boundary data, as well as the temperature and displacement inside a body from over-specified boundary data measured on an accessible portion of its boundary. The problem is linear but ill-posed. The uniqueness of the solution is established but the continuous dependence on the input data is violated. In order to reconstruct a stable and accurate solution, the method of fundamental solutions is combined with Tikhonov regularization where the regularization parameter is selected based on the L-curve criterion. Numerical results are presented in both two and three dimensions showing the feasibility and ease of implementation of the proposed technique.     

A mathematical model for vehicle routing problem under endogenous uncertainty

In this study, a multistage stochastic programming (SP) model is presented for a variant of single-vehicle routing problem with stochastic demands from a dynamic viewpoint. It is assumed that the actual demand of a customer becomes known only when the customer is visited. This problem falls into the category of SP with endogenous uncertainty and hence, the scenario tree is decision-dependent. Therefore, nonanticipativity of decisions is ensured by conditional constraints making up a large portion of total constraints. Thus, a novel approach is proposed that considerably reduces the problem size without any effect on the solution space. Computational results on some test problems are reported.     

Reconstructing design parameters of a rectangular resonator via peak signal-to-noise ratio and global optimization algorithms

This article proposes an approach for reconstructing physical parameters of a sample in a rectangular resonator during microwave radiation, knowing a priori, its electric field distribution. The inverse problem was solved using two global optimization algorithms and the peak signal-to-noise ratio (PSNR) criterion. First, the Self-regulated Fretwidth Harmony Search algorithm (SFHS) identified suitable resonant frequencies for a given configuration. Next, the unified Particle Swarm Optimization (UPSO) optimized said configuration. Together, they became a maximization strategy of the PSNR through a dual optimization process. Results showed the ability of the approach for estimating the height of each sample block and the resonating frequency of the cavity. This process takes longer to finish as a higher PSNR is demanded (mainly due to the aforementioned dual optimization). Even so, it allows for more similar electric field distributions between both, the direct and inverse problems.     

关于搞好士官学员思想教育的几点思考

本文着重从士官学员的思想特点及其发展变化规律入手,研究如何针对这些特点和规律搞好思想教育工作。