交叉规划与双层规划的经济背景差异分析

本文分析了交叉规划问题与双层规划问题的实际经济背景,重点讨论了这两类问题解之间的不同经济意义．指出双层规划刻画的是两个经济行为人之间的主从属关系,而交叉规划刻画的则是两个经济行为人之间的平等互利关系     

无正则性条件下的一个信赖域方法的全局收敛性

1.引 言考虑下列等式约束最优化问题:min f(x)x∈Rn (1.1)s.t.C(x)=0其中f:Rn→R,C（x）=（c1（x）,C2（x）,…,Cm（x））T,Ci:Rn→R,（i=1,…,m）.我们假设f（x）,Ci（x）（i=1,2,…,m）是连续可微函数.令g（x）=　f（x）,A（x）=　C（x）T.为了方便,我们通常用 Ck,fk,gk,Ak分别表示 C（xk）,f（xk）,g（xk）A（xk）. SQP方法是一迭代方法.在 xk点,通过解下列子问题来得到搜索方向 dk     

一种用硬件实现的Bayer格式图像恢复算法

针对传统的双线性Bayer彩色图像恢复算法恢复效果不理想,边界部分不明显,局部图像有团块等问题,提出了一种基于硬件实现的Bayer图像快速插值算法。采用梯度算法对Bayer格式图像绿色通道进行恢复,根据像素点所属的颜色组对蓝色通道进行恢复。实验结果表明,本文算法比双线性法有更好的峰值信噪比(PSNR)值,RGB 3个通道的PSNR值均比双线性法高5 dB以上,而且算法消耗时间比双线性法少,恢复的图像视觉效果更好。实验处理一幅512×512的全彩图像仅需要9.3 ms,完全可以满足实时性的要求,因此,本文算法在对实时性要求高的场合有很好的应用前景。     

Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems

As indicated by the most widely accepted classification, the Multi-Objective Mathematical Programming (MOMP) methods can be classified as a priori, interactive and a posteriori, according to the decision stage in which the decision maker expresses his/her preferences. Although the a priori methods are the most popular, the interactive and the a posteriori methods convey much more information to the decision maker. Especially, the a posteriori (or generation) methods give the whole picture (i.e. the Pareto set) to the decision maker, before his/her final choice, reinforcing thus, his/her confidence to the final decision. However, the generation methods are the less popular due to their computational effort and the lack of widely available software. The present work is an effort to effectively implement the ε-constraint method for producing the Pareto optimal solutions in a MOMP. We propose a novel version of the method (augmented ε-constraint method - AUGMECON) that avoids the production of weakly Pareto optimal solutions and accelerates the whole process by avoiding redundant iterations. The method AUGMECON has been implemented in GAMS, a widely used modelling language, and has already been used in some applications. Finally, an interactive approach that is based on AUGMECON and eventually results in the most preferred Pareto optimal solution is also proposed in the paper.     

模糊多目标半定规划的最优性条件

将模糊集理论应用到多目标半定规划中来,提出了有约束的模糊多目标半定规划模型,并首次给出了其最优有效解的定义.通过构造确定的隶属度函数,将以矩阵为决策变量的模糊多目标半定规划转化为一种目标函数的某些分量由约束函数决定的确定性多目标半定规划,并证明了前者最优有效解与后者有效解的一致性.在此基础之上,讨论了二者的最优性条件.     

一类全系数模糊线性规划的求解方法

利用结构元方法定义一种模糊数排序准则,提出将目标函数和约束条件中都含有三角模糊数的全系数模糊线性规划等价转化为经典线性规划的方法,并证明其合理性.与其它方法相比较,该方法证明了得到的解优于已有其它方法的解,并且约束条件少,运算方法简便.将本文的方法运用到数值算例中,进一步表明了提出方法的有效性和广泛性.     

A novel algorithm to integrate synchronous digital hierarchy networks into Optical Transport Network using mixed line rates

In this era of high data transfer speeds and new age technologies, Optical Transport Network (OTN) along with its newly introduced Optical Transport Hierarchy (OTH) has provided a lease of life to legacy low rate networks. It has provided a common backbone for multiple data rates to coexist on same fiber along with the enhanced transmission reach. The cost effective Optical Transport Network design has always been a complex issue due to the presence of multiple variables like number of fibers on each link, available data rates on each fiber, the wavelength count, transmission reach at each data rate, etc. In this paper an Integer Linear Programming (ILP) model has been presented to solve Routing problem for Synchronous Digital Hierarchy (SDH) over OTN over DWDM design. Optical Transport Hierarchy (OTH) has been used to integrate heterogenous SDH/SONET operating at different rates (STM-16, STM-64 and STM-256) into a single network supporting mixed line rates. These rates can coexist in a same fiber but each rate carries different cost with it. The objective function aims at finding the least cost routing solution by looking at different tradeoffs between the Capital Expenditure and the operational expenditure. Certainly different variables like the number of fibers and wavelengths, transmission reach, etc. are a factor in it. A mechanism has been put to monitor the Bit Error Rate (BER) levels as well. For evaluating the ILP model, 18 Node 38 Link European Optical Network was considered as the reference model and two ordering techniques, namely, full ILP and highest rate first (HRF) were used for deriving the results. The ILP model was designed with minimum of decision variables so in spite of big reference network it converges much faster. Under the given conditions, full ILP gave least cost network whereas HRF ordering took least time for ILP to converge.     

Invex nonsmooth alternative theorem and applications *

An invex constrained nonsmooth optimization problem is considered, in which the presence of an abstract constraint set is possibly allowed. Necessary and sufficient conditions of optimality are provided and weak and strong duality results established. Following Geoffrion’s approach an invex nonsmooth alternative theorem of Gordan type is then derived. Subsequently, some applications on multiobjective programming are then pursued     

Generalized semi-infinite programming: numerical aspects

Generalized semi-infinite optimization problems (GSIP) are considered. It is investigated how the numerical methods for standard semi-infinite programming (SIP) can be extended to GSIP. Newton methods can be extended immediately. For discretization methods the situation is more complicated. These difficulties are discussed and convergence results for a discretization- and an exchange method are derived under fairly general assumptions on GSIP. The question is answered under which conditions GSIP represents a convex problem.     

Realtime control of robots with initial value perturbations via nonlinear programming methods

The mathematical model of an industrial robot with initial value perturbations is considered as a parametric nonlinear control problem subject to control and state constraints. Based on recent stability results for parametric control problems, a robust nonlinear programming method is proposed for computing the sensitivity derivatives of optimal solutions. Real-time control approximations of perturbed optimal solutions are obtained by evaluating a first order Taylor expansion of the perturbed solution. The efficiency of the real-time approximation is demonstrated for the robot model