一种确定性时变系统离散时间自适应控制算法

研究实时控制的自校正控制算法问题的运用是近年来人们很感兴趣的问题,在自适应控制中,特别在飞行器控制系统中,经常会遇到快速时变参数的辩识问题,然而现有的方法大都适用于参数缓慢时变的系统,本文提出一种新的方法,它能成功地控制快速时变参数的未知系统,同时给出了一些仿真计算,得到了令人满意的结果。     

基于遗传算法的湿陷性黄土地基灰土挤密桩优化设计

利用Visual C＋＋语言，定义了一个面向对象的基于实数编码遗传算法类。运用可最大限度保证遗传算法搜索到问题的全局最优解的深度搜索策略，编制了灰土挤密桩的优化设计和造价估算遗传算法程序，并针对兰州某地灰土挤密桩复合地基进行了计算分析，并与原有方案比较，结果表明：两种优化方案在满足承载力和变形的条件下，在降低造价成本方面优势非常明显。     

面向多最优解组合优化问题的决策求解算法

针对具有固定物品总和、多最优解特征的组合优化问题,以固定总和实数子集问题和购买鸡翅问题为例,给出了这类多最优解组合优化问题的形式化表示。在分析枚举等经典算法基础上,提出了基于整数状态表示和实数状态表示的0-1决策递归搜索多最优解动态规划算法。针对该算法在最优解数量较大时,时间复杂度趋向O(mⁿ)的问题,提出了基于相同决策路径合并和基于0-x决策的两种改进算法。实验中两种改进算法的计算时间基本符合与O(nb+nm)的正比关系,表明对于这类多最优解组合优化问题具有良好的求解性能。     

两种轰炸弹道快速积分算法的比较

利用数学仿真,测试了两种轰炸弹道快速积分方法：中国湖算法和极坐标算法,后者是西北工业大学（ＮＰＵ）开发的。对某型航弹的弹道诸元解算的结果表明,无论是精度还是实时计算量,后者都优于前者甚多。     

一种确定性时变系统离散时间自适应控制算法

研究实时控制的自校正控制算法问题的运用是近年来人们很感兴趣的问题,在自适应控制中,特别在飞行器控制系统中,经常会遇到快速时变参数的辩识问题,然而现有的方法大都适用于参数缓慢时变的系统,本文提出一种新的方法,它能成功地控制快速时变参数的未知系统,同时给出了一些仿真计算,得到了令人满意的结果。     

几种机动目标运动模型的跟踪性能对比

机动目标跟踪是目标定位与跟踪领域研究的难点问题之一.在分析Singer模型、"当前"统计模型、速度估计自适应模型的基础上,对这三种模型及算法进行仿真,给出了上述三种模型跟踪机动目标的精度与实时性的比较结果.     

纯方位目标运动分析的一种系统方法

本文首先对以往关于纯方位目标运动分析的研究作了系统性的综述,阐明了以往发展的纯方位TMA算法所存在的共性不足以及解决该问题的困难性,最后介绍了我们研究的一种系统解决纯方位TMA问题的DL原理。     

Integrated scheduling of loading and transportation with tractors and semitrailers separated

Motivated by some practical applications, we study a new integrated loading and transportation scheduling problem. Given a set of jobs, a single crane is available to load jobs, one by one, onto semitrailers with a given capacity. Loaded semitrailers are assigned to tractors for transportation tasks. Subject to limited resources (crane, semitrailers, and tractors), the problem is to determine (1) an assignment of jobs to semitrailers for loading tasks, (2) a sequence for the crane to load jobs onto semitrailers, (3) an assignment of loaded semitrailers to tractors for transportation tasks, and (4) a transportation schedule of assigned tractors such that the completion time of the last transportation task is minimized. We first formulate the problem as a mixed integer linear programming model (MILPM) and prove that the problem is strongly NP‐hard. Then, optimality properties are provided which are useful in establishing an improved MILPM and designing solution algorithms. We develop a constructive heuristic, two LP‐based heuristics, and a recovering beam search heuristic to solve this problem. An improved procedure for solutions by heuristics is also presented. Furthermore, two branch‐and‐bound (B&B) algorithms with two different lower bounds are developed to solve the problem to optimality. Finally, computational experiments using both real data and randomly generated data demonstrate that our heuristics are highly efficient and effective. In terms of computational time and the number of instances solved to optimality in a time limit, the B&B algorithms are better than solving the MILPM. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 416–433, 2015     

Partitioning of biweighted trees

A districting problem is formulated as a network partitioning model where each link has one weight to denote travel time and another weight to denote workload. The objective of the problem is to minimize the maximum diameter of the districts while equalizing the workload among the districts. The case of tree networks is addressed and efficient algorithms are developed when the network is to be partitioned into two or three districts. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 143–158, 2002; DOI 10.1002/nav.10003     

Hybrid heuristics for minimum cardinality set covering problems

Minimum cardinality set covering problems (MCSCP) tend to be more difficult to solve than weighted set covering problems because the cost or weight associated with each variable is the same. Since MCSCP is NP-complete, large problem instances are commonly solved using some form of a greedy heuristic. In this paper hybrid algorithms are developed and tested against two common forms of the greedy heuristic. Although all the algorithms tested have the same worst case bounds provided by Ho [7], empirical results for 60 large randomly generated problems indicate that one algorithm performed better than the others.     

基于遗传算法的大系统可靠度优化分配

给出了大系统可靠度优化分配的数学模型 ,设计了大系统可靠度优化分配问题的遗传算法。数值例子表明该方法可以有效地解决大规模的、复杂的非线性规划问题。解决了传统算法的局限性     

混合尺寸目标电磁计算的时域伪谱/有限体积混合方法

针对单一算法对混合尺寸目标进行时域电磁分析的困难,提出一种时域伪谱(PSTD)同时域有限体积(FVTD)混合方法。FVTD可方便地分析复杂的几何结构和材料,但是难以计算电大尺寸的目标,PSTD则特别适合计算电大尺寸的规则结构,但在模拟复杂的几何结构尤其是带有曲边结构以及电大、电小共存结构时存在困难。混合方法克服了单独算法的缺点,融合各自的优势,提高了算法的求解能力和应用范围。为了减小两种算法连接边界带来的反射,采用了FVTD计算面均值的二次函数重构方法,给出了交叠网格和非交叠网格两种混合方案。数值试验表明,混合方法有较高的精度,具有时域分析混合尺寸目标电磁问题的能力。     

An n-step, 2-variable search algorithm for the component placement problem

The component placement problem is a specialization of the quadratic assignment problem that has been extensively studied for a decade and which is of considerable practical value. Recently, interest in component placement algorithms has risen primarily as a result of increased activity in the field of computer-aided design automation. This paper deals with the methodology of component placement and is based on the results of considerable operational experience. A tutorial presentation of tree search placement algorithms is provided, and an improved placement procedure is described which is demonstrated to be effective in generating near optimal solutions to the component placement problem. These solutions are completely reproducible and are obtained at an acceptable expenditure of computational resources. An additional objective is an assessment of performance of the class of near optimal algorithms. In particular, the question- how close to optimal are the near optimal solutions- is examined.     

P2P系统中数据复制算法研究

比较分析了P2P系统中各种数据复制算法,并提出了一种基于LDPC编码的数据复制算法Dyre,数据块采用动态分配算法存储到节点中,在节点邻居中保存数据块的副本以提高数据块的有效性,数据块的数量过小时重建数据块。实验表明,即使节点的可靠性非常低,该算法也能够获得很高的数据可用性。     

Revenue maximization in two-station tandem queueing systems

We study optimal pricing for tandem queueing systems with finite buffers. The service provider dynamically quotes prices to incoming price sensitive customers to maximize the long-run average revenue. We present a Markov decision process model for the optimization problem. For systems with two stations, general-sized buffers, and two or more prices, we describe the structure of the optimal dynamic pricing policy and develop tailored policy iteration algorithms to find an optimal pricing policy. For systems with two stations but no intermediate buffer, we characterize conditions under which quoting either a high or a low price to all customers is optimal and provide an easy-to-implement algorithm to solve the problem. Numerical experiments are conducted to compare the developed algorithms with the regular policy iteration algorithm. The work also discusses possible extensions of the obtained results to both three-station systems and two-station systems with price and congestion sensitive customers using numerical analysis.     

Optimal schedules for special structure flowshops

This paper considers the problem of scheduling a given number of jobs on a specified number of machines in a flowshop where the objective function is to minimize the total throughput time in which all jobs complete processing on all machines. Based on the combinatorial analysis of the problem, several simple algorithms are developed for solving special structure flowshop scheduling problems where the process times are not completely random, but bear a well-defined relationship to one another. The proposed algorithms are both simple and computationally efficient and can optimally solve large-sized problems even with manual computational devices.     

On the equivalence of three approximate continuous review inventory models

This paper considers the problem of computing reorder points and order quantities for continuous review inventory systems subject to either a service level constraint or a constraint on the average fraction of time out of stock. It is demonstrated that three apparently distinct models are equivalent under these circumstances. Using this equivalence, streamlined algorithms for computed lot sizes and recorder points are developed.     

基于平稳小波变换的遥感图像融合方法

针对目前方法在多光谱图像和高分辨率图像融合中存在的问题,提出了一种IHS交换和平稳小波变换相结合的图像融合方法.首先对多光谱图像进行IHS变换后,得到I、H和S三个分量,接着对I分量和高分辨率图像进行基于平稳小波变换的图像融合,得到一幅新的强度图像,最后用新的强度图像和H及S进行IHS反变换,进而获得最终融合图像.实验表明,它优于传统的IHS变换法和小波变换法.     

Optimization of schedule stability and efficiency under processing time variability and random machine breakdowns in a job shop environment

The ability to cope with uncertainty in dynamic scheduling environments is becoming an increasingly important issue. In such environments, any disruption in the production schedule will translate into a disturbance of the plans for several external activities as well. Hence, from a practical point of view, deviations between the planned and realized schedules are to be avoided as much as possible. The term stability refers to this concern. We propose a proactive approach to generate efficient and stable schedules for a job shop subject to processing time variability and random machine breakdowns. In our approach, efficiency is measured by the makespan, and the stability measure is the sum of the variances of the realized completion times. Because the calculation of the original measure is mathematically intractable, we develop a surrogate stability measure. The version of the problem with the surrogate stability measure is proven to be NP‐hard, even without machine breakdowns; a branch‐and‐bound algorithm is developed for this problem variant. A tabu search algorithm is proposed to handle larger instances of the problem with machine breakdowns. The results of extensive computational experiments indicate that the proposed algorithms are quite promising in performance. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

程序进化器

研究用模拟进化方法进行程序设计的途径。构造了以形式文法为遗传表示的程序进化器,提出了这个进化器使用的有关算法。本文用程序进化器解决了人工蚁问题。