Coordinated replenishments from multiple suppliers with price discounts

In this study we present an integer programming model for determining an optimal inbound consolidation strategy for a purchasing manager who receives items from several suppliers. The model considers multiple suppliers with limited capacity, transportation economies, and quantity discounts. We propose an integrated branch and bound procedure for solving the model. This procedure, applied to a Lagrangean dual at every node of the search tree, combines the subgradient method with a primal heuristic that interact to change the Lagrangean multipliers and tighten the upper and lower bounds. An enhancement to the branch and bound procedure is developed using surrogate constraints, which is found to be beneficial for solving large problems. We report computational results for a variety of problems, with as many as 70,200 variables and 3665 constraints. Computational testing indicates that our procedure is significantly faster than the general purpose integer programming code OSL. A regression analysis is performed to determine the most significant parameters of our model. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 579–598, 1998     

A specially structured nonlinear integer resource allocation problem

We present an algorithm for solving a specially structured nonlinear integer resource allocation problem. This problem was motivated by a capacity planning study done at a large Health Maintenance Organization in Texas. Specifically, we focus on a class of nonlinear resource allocation problems that involve the minimization of a convex function over one general convex constraint, a set of block diagonal convex constraints, and bounds on the integer variables. The continuous variable problem is also considered. The continuous problem is solved by taking advantage of the structure of the Karush‐Kuhn‐Tucker (KKT) conditions. This method for solving the continuous problem is then incorporated in a branch and bound algorithm to solve the integer problem. Various reoptimization results, multiplier bounding results, and heuristics are used to improve the efficiency of the algorithms. We show how the algorithms can be extended to obtain a globally optimal solution to the nonconvex version of the problem. We further show that the methods can be applied to problems in production planning and financial optimization. Extensive computational testing of the algorithms is reported for a variety of applications on continuous problems with up to 1,000,000 variables and integer problems with up to 1000 variables. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 770–792, 2003.     

宽带模糊函数的群论解释及小波变换求解

讨论了各种形式的宽带模糊函数,通过群论分析表明,它们都可解释为二维不可约仿射群U表示的矩阵系数,因此其性质可通过对仿射群的研究作出解释。还讨论了宽带模糊函数与小波变换的关系,并由此导出其高效的小波变换求解方法。     

整数线性规划问题的一个新算法

本文给出求解整数线性规划问题的一个算法。基本思想是通过求出其伴随线性规划问题的最优单纯形表,把整数线性规划化成正整数系数的不定方程,然后从不定方程的非负整数解集中选取一组满足整数线性规划的约束条件的解,作为整数线性规划的最优解。     

一种适用于长基线的改进CIR算法

长基线下,受伪距多径和电离层残差影响,传统的CIR法解算载波相位宽巷模糊度时某些历元无法得到正确的结果,基础载波模糊度的搜索范围也较大。分析了CIR法的模糊度误差,提出了基于载波相位平滑伪距并且消除电离层时延的改进的CIR算法,分析了其误差方差,最后利用Compass系统实测数据对短基线和长基线两种情况下CIR法和改进CIR法的解算结果进行比较。实测数据表明,本文提出的算法能够单历元解算超宽巷模糊度和宽巷模糊度,并且能够大大缩小基础载波模糊度的搜索空间。     

一种新的星载高分辨宽测绘带SAR运动目标

本文针对星载多通道高分辨宽测绘带合成孔径雷达系统,提出了一种地面运动目标检测和参数估计方法,该方法首先利用空时自适应处理进行杂波抑制,然后采用传统SAR成像处理得到模糊的运动目标图像,接着利用恒虚警检测技术检测出所有运动目标,包括真实目标和由于多普勒模糊引起的虚假目标,再根据模糊图像的空间位置关系从所有成像目标中检测出运动目标的真实成像位置,最后根据运动目标的斜距历程得到因运动目标速度引起的图像位置偏移,由此估计得到运动目标速度。该方法具有运算量小、检测精度高等优点,星载仿真数据验证了本文方法有效性。     

一种利用GPS载波相位姿态测量的方法

GPS初始整周模糊度的求解是利用载波相位进行测量时的关键问题.采用了对系数矩阵进行QR分解的方法,用以降低矩阵的维数.模糊度搜索时,针对Z变换可能会引入多余误差,采用了对称三角分解法对协方差矩阵进行去相关处理.实验与仿真结果表明,定位误差在0.5 cm以内,方位角和仰角误差在0.1°以内.     

基于线性反时间混沌理论的混沌信号模糊函数算法

从线性反时间混沌理论出发,提出一种混沌信号宽带模糊函数算法。在现有的宽带模糊函数算法中,时间尺度变换的混沌信号需要极大的运算量来得到,难以适应需要实时处理的工程环境。根据反时间混沌理论,噪声脉冲驱动下的线性系统能产生反时间混沌信号。通过不同时钟频率的数字系统产生脉冲信号,然后以此脉冲信号驱动相应的线性系统直接产生延迟和时间尺度变换后的反时间混沌信号,最后可通过相关处理方便地计算相应混沌信号的宽带模糊函数。通过理论推导和数值仿真阐述及分析该模糊函数算法,证明了该方法数字模拟混合的结构使其能方便应用于实际的工程之中。     

Route optimization for multiple searchers

We consider a discrete time‐and‐space route‐optimization problem across a finite time horizon in which multiple searchers seek to detect one or more probabilistically moving targets. This article formulates a novel convex mixed‐integer nonlinear program for this problem that generalizes earlier models to situations with multiple targets, searcher deconfliction, and target‐ and location‐dependent search effectiveness. We present two solution approaches, one based on the cutting‐plane method and the other on linearization. These approaches result in the first practical exact algorithms for solving this important problem, which arises broadly in military, rescue, law enforcement, and border patrol operations. The cutting‐plane approach solves many realistically sized problem instances in a few minutes, while existing branch‐and‐bound algorithms fail. A specialized cut improves solution time by 50[percnt] in difficult problem instances. The approach based on linearization, which is applicable in important special cases, may further reduce solution time with one or two orders of magnitude. The solution time for the cutting‐plane approach tends to remain constant as the number of searchers grows. In part, then, we overcome the difficulty that earlier solution methods have with many searchers. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

自然语言形式化研究中几个基本问题的再认识

针对目前自然语言形式化研究中存在的问题 ,就歧义性、形式化与系统模型等几个基本问题做了进一步的分析与讨论。认为 :歧义性有狭义与广义之分 ,有层次之分 ,又有形式化与非形式化之分 ,确定它们的界线是很重要的。如何使系统体现出自然语言的个性化是目前形式化研究中应引起注意的一个关键问题 ,为此还提出一个系统结构模型。