Interdiction models for delaying adversarial attacks against critical information technology infrastructure

Information technology (IT) infrastructure relies on a globalized supply chain that is vulnerable to numerous risks from adversarial attacks. It is important to protect IT infrastructure from these dynamic, persistent risks by delaying adversarial exploits. In this paper, we propose max‐min interdiction models for critical infrastructure protection that prioritizes cost‐effective security mitigations to maximally delay adversarial attacks. We consider attacks originating from multiple adversaries, each of which aims to find a “critical path” through the attack surface to complete the corresponding attack as soon as possible. Decision‐makers can deploy mitigations to delay attack exploits, however, mitigation effectiveness is sometimes uncertain. We propose a stochastic model variant to address this uncertainty by incorporating random delay times. The proposed models can be reformulated as a nested max‐max problem using dualization. We propose a Lagrangian heuristic approach that decomposes the max‐max problem into a number of smaller subproblems, and updates upper and lower bounds to the original problem via subgradient optimization. We evaluate the perfect information solution value as an alternative method for updating the upper bound. Computational results demonstrate that the Lagrangian heuristic identifies near‐optimal solutions efficiently, which outperforms a general purpose mixed‐integer programming solver on medium and large instances.     

粒子PHD滤波存活粒子采样新方法

针对多目标跟踪粒子概率假设密度滤波算法中存活粒子的重要性密度采样问题,给出一种结合最新量测信息的存活粒子重要性密度采样新方法.该方法根据最新量测集中的各个最测与目标粒子的单步预测状态的似然值,以概率选取量测值,利用无迹变换获得粒子的重要性密度函数,并对其进行采样实现粒子概率假设密度滤波中存活粒子的采样,有效地减轻了粒子的退化现象. 3目标跟踪仿真试验中,当目标模型与跟踪算法使用的目标模型不匹配时,采用所提出的存活粒子采样方法的粒子概率假设密度滤波算法最优子模式分配距离下降约70km.论文给出的存活粒子采样新方法显著地提高了多目标跟踪粒子概率假设密度滤波算法的鲁棒性.     

Distribution free bounds for service constrained (Q,r) inventory systems

A classical and important problem in stochastic inventory theory is to determine the order quantity (Q) and the reorder level (r) to minimize inventory holding and backorder costs subject to a service constraint that the fill rate, i.e., the fraction of demand satisfied by inventory in stock, is at least equal to a desired value. This problem is often hard to solve because the fill rate constraint is not convex in (Q, r) unless additional assumptions are made about the distribution of demand during the lead‐time. As a consequence, there are no known algorithms, other than exhaustive search, that are available for solving this problem in its full generality. Our paper derives the first known bounds to the fill‐rate constrained (Q, r) inventory problem. We derive upper and lower bounds for the optimal values of the order quantity and the reorder level for this problem that are independent of the distribution of demand during the lead time and its variance. We show that the classical economic order quantity is a lower bound on the optimal ordering quantity. We present an efficient solution procedure that exploits these bounds and has a guaranteed bound on the error. When the Lagrangian of the fill rate constraint is convex or when the fill rate constraint does not exist, our bounds can be used to enhance the efficiency of existing algorithms. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 635–656, 2000     

多目标的分布式协同进化MDO算法

通过引入非优超排序和排挤的多目标处理机制 ,将分布式协同进化MDO算法的能力扩展到多目标的多学科设计优化问题。多目标的分布式协同进化MDO算法在保持各学科充分自治和各学科并行设计优化协同的基础上 ,通过一次运行即可获得具有良好分布的多个Pareto最优解 ,逼近整个Pareto最优前沿。应用于导弹气动 /发动机 /控制三学科两目标设计优化问题 ,与约束法计算结果的对比表明算法能够有效逼近该问题的Pareto最优前沿 ,为设计决策提供了丰富的信息     

Iterative coloring extension of a maximum clique

In this paper we present an improved branch and bound algorithm for the vertex coloring problem. The idea is to try to extend the coloring of a maximum clique to its adjacent vertices. If this succeeds, its successive neighbors are considered; in case of failure (i.e., in the case the initial colors are not sufficient), working on the subgraph induced by the maximum clique and its neighborhood, the lower bound is improved by seeking for an optimal coloring of this subgraph by branch and bound. The process is repeated iteratively until the whole graph is examined. The iterative scheme exploits a further lower bound obtained by integrating a simple algorithm into the maximum clique search, and a new method to compute upper bounds on subgraphs. Furthermore, a new branching rule and a method for the selection of the initial maximum clique are presented. Extensive computational results and comparisons with existing exact coloring algorithms on random graphs and benchmarks are given. © 2001 John Wiley & Sons, Inc. Naval Research Logistic 48: 518–550, 2001     

基于信息熵TOP SIS法的无线传感器网络节点自定位技术

在无线传感器网络的应用中，节点的定位是一个关键的问题。但是，利用已知节点对未知节点定位的算法存在着定位精度不高，定位计算量大等缺点。针对该问题，提出了一种基于信息熵TOPSIS法的节点自定位算法，该算法利用TOPSIS法按已给的传感器属性进行排序，只取最靠前的3个节点代入标准最小二乘公式中进行计算，既缩短了计算时间，又保证了计算精度。仿真实验证明，该算法是一种有效可行的算法。     

New product introduction against a predator: A bilevel mixed‐integer programming approach

We consider a scenario with two firms determining which products to develop and introduce to the market. In this problem, there exists a finite set of potential products and market segments. Each market segment has a preference list of products and will buy its most preferred product among those available. The firms play a Stackelberg game in which the leader firm first introduces a set of products, and the follower responds with its own set of products. The leader's goal is to maximize its profit subject to a product introduction budget, assuming that the follower will attempt to minimize the leader's profit using a budget of its own. We formulate this problem as a multistage integer program amenable to decomposition techniques. Using this formulation, we develop three variations of an exact mathematical programming method for solving the multistage problem, along with a family of heuristic procedures for estimating the follower solution. The efficacy of our approaches is demonstrated on randomly generated test instances. This article contributes to the operations research literature a multistage algorithm that directly addresses difficulties posed by degeneracy, and contributes to the product variety literature an exact optimization algorithm for a novel competitive product introduction problem. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

A forward network simplex algorithm for solving multiperiod network flow problems

An optimization model which is frequently used to assist decision makers in the areas of resource scheduling, planning, and distribution is the minimum cost multiperiod network flow problem. This model describes network structure decision-making problems over time. Such problems arise in the areas of production/distribution systems, economic planning, communication systems, material handling systems, traffic systems, railway systems, building evacuation systems, energy systems, as well as in many others. Although existing network solution techniques are efficient, there are still limitations to the size of problems that can be solved. To date, only a few researchers have taken the multiperiod structure into consideration in devising efficient solution methods. Standard network codes are usually used because of their availability and perceived efficiency. In this paper we discuss the development, implementation, and computational testing of a new technique, the forward network simplex method, for solving linear, minimum cost, multiperiod network flow problems. The forward network simplex method is a forward algorithm which exploits the natural decomposition of multiperiod network problems by limiting its pivoting activity. A forward algorithm is an approach to solving dynamic problems by solving successively longer finite subproblems, terminating when a stopping rule can be invoked or a decision horizon found. Such procedures are available for a large number of special structure models. Here we describe the specialization of the forward simplex method of Aronson, Morton, and Thompson to solving multiperiod network network flow problems. Computational results indicate that both the solution time and pivot count are linear in the number of periods. For standard network optimization codes, which do not exploit the multiperiod structure, the pivot count is linear in the number of periods; however, the solution time is quadratic.     

A two product dynamic economic lot size production model with either-or production constraints

This paper considers the production of two products with known demands over a finite set of periods. The production and inventory carrying costs for each product are assumed to be concave. We seek the minimum cost production schedule meeting all demands, without backlogging, assuming that at most one of the two products can be produced in any period. The optimization problem is first stated as a nonlinear programming problem, which allows the proof of a result permitting the search for the optimal policy to be restricted to those which produce a product only when its inventory level is zero. A dynamic programming formulation is given and the model is then formulated as a shortest route problem in a specially constructed network.     

A method for solving the transportation problem

A new method has been developed f o r solving the transportation problem. This method is a modification and a generalization of the method for solving the multiple assignment problem developed by Dr. A. J. Hoffman and Dr. H. M. Markowitz. This method is of interest for several reasons. In the first place it is significantly different from all other methods for solving the trans -portation problem known to the author. Secondly, it is moderately simple touse and understand. Thirdly, and perhaps most important, it has proved to be very adaptable tri high-speed computer operations. It is now being used by several branches of the armed services.     

Time-minimizing transportation problems

A method is given for finding those solutions of a transportation problem which minimize the total time necessary for transporting goods from the suppliers to the consumers. Several extensions of the model are presented.     

多功能雷达建模中的雷达字提取技术研究

雷达字为有限数目脉冲的固定排列,能够反映多功能雷达的工作状态和威胁等级。针对漏脉冲和虚假脉冲所造成的雷达字不能正确提取的问题,提出了一种基于三级匹配的雷达字提取算法。该算法首先对分选后的辐射源脉冲列进行数据库级的匹配过滤,确定模板雷达范围,然后分别利用脉冲配对和序列相关技术进行精确识别。仿真实验表明,该方法不仅能提取多功能雷达辐射源的雷达字,而且对噪声环境具有较好的适应能力。     

Disruption management in production planning

We study the problem of recovering a production plan after a disruption, where the disruption may be caused by incidents such as power failure, market change, machine breakdown, supply shortage, worker no‐show, and others. The new recovery plan we seek after has to not only suit the changed environment brought about by the disruption, but also be close to the initial plan so as not to cause too much customer unsatisfaction or inconvenience for current‐stage and downstream operations. For the general‐cost case, we propose a dynamic programming method for the problem. For the convex‐cost case, a general problem which involves both cost and demand disruptions can be solved by considering the cost disruption first and then the demand disruption. We find that a pure demand disruption is easy to handle; and for a pure cost disruption, we propose a greedy method which is provably efficient. Our computational studies also reveal insights that will be helpful to managing disruptions in production planning. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

On some sequencing problems

The (mxn) sequencing problem may be characterized as follows: There are m machines which can produce a piece consisting of n parts. Each part has a determined order in which it is processed through the machines. It is assumed that each machine cannot deal with more than one part at a time and that the processing required for each part can be accomplished only on one machine. That is, the machines are all specialized so that alternate machines for the same processing on a part is not possible. The problem is to find the best production plan consisting in sequencing the different parts so as to make the whole amount of time from the beginning of work till the piece is completed the shortest possible. Such a plan is called an optimum one. In the first 4 sections of this paper, the problem (2xn) is solved for the (2xn) case in which the order in which parts come on the machine is not constrained by further assumptions. The remainder of the paper then takes up: 1) the (3xn) problem of Bellman-Johnson (viz. the technological processing order through the machine is the same for all parts) for several new special cases; 2) the 2xn problem of sequencing when delay times must also be considered; and, 3) some properties of an approximating method for solving (mxn) problems, including a delineation of cases when the approximating method will yield optimal solutions.     

Constant risk aversion in stochastic contests with exponential completion times

This article analyzes a class of stochastic contests among multiple players under risk‐averse exponential utility. In these contests, players compete over the completion of a task by simultaneously deciding on their investment, which determines how fast they complete the task. The completion time of the task for each player is assumed to be an exponentially distributed random variable with rate linear in the player's investment and the completion times of different players are assumed to be stochastically independent. The player that completes the task first earns a prize whereas the remaining players earn nothing. The article establishes a one‐to‐one correspondence between the Nash equilibrium of this contest with respect to risk‐averse exponential utilities and the nonnegative solution of a nonlinear equation. Using the properties of the latter, it proves the existence and the uniqueness of the Nash equilibrium, and provides an efficient method to compute it. It exploits the resulting representation of the equilibrium investments to determine the effects of risk aversion and the differences between the outcome of the Nash equilibrium and that of a centralized version.© 2016 Wiley Periodicals, Inc. Naval Research Logistics 66:4–14, 2019     

基于复—方向小波变换和视觉表示的图像增强

针对复—方向小波变换具有好的平移不变性、方向选择性、对图像边缘特征的表示比传统实小波要好等优势,提出了一种基于视觉表示统计特性和复—方向小波变换的图像增强新方法。该算法在图像的多尺度复—方向小波变换域内进行动态范围(亮度)修正和局部对比度调整以增强图像。实验结果表明,与目前经典的多尺度增强算法相比,运用本文的算法增强的图像视觉效果好,在边缘和细节处失真小,而且对图像源的变化具有很好的鲁棒性。     

Continuous-time markov decision processes with nonzero terminal reward

In this article we consider a continuous-time Markov decision process with a denumerable state space and nonzero terminal rewards. We first establish the necessary and sufficient optimality condition without any restriction on the cost functions. The necessary condition is derived through the Pontryagin maximum principle and the sufficient condition, by the inherent structure of the problem. We introduce a dynamic programming approximation algorithm for the finite-horizon problem. As the time between discrete points decreases, the optimal policy of the discretized problem converges to that of the continuous-time problem in the sense of weak convergence. For the infinite-horizon problem, a successive approximation method is introduced as an alternative to a policy iteration method.     

开弧段外Laplace方程单层位势解法探讨

由Laplace方程Dirichlet问题产生的第一类积分方程的核具有对数奇异性,并 且积分方程的解在开弧段端点处具有r-1/2的奇异性。为了克服奇异积分计算的困难,将这 种对数奇异性分离出来使用解析积分,其余部分使用数值积分。并用单层位势方法得到该 问题解的近似表达式。     

The use of dynamic programming methodology for the solution of a class of nonlinear programming problems

This paper presents an application of a method for finding the global solution to a problem in integers with a separable objective function of a very general form. This report shows that there is a relationship between an integer problem with a separable nonlinear objective function and many constraints and a series of nonlinear problems with only a single constraint, each of which can be solved sequentially using dynamic programming. The first solution to any of the individual smaller problems that satisfies the original constraints in addition, will be the optimal solution to the multiply-constrained problem.     

一种分析广义脊形传输器件的新型数值方法

利用Compact 2-D频域有限差分(FDFD)法分析广义脊形传输器件特性,得到的本征方程只涉及4个横向场分量,与同时处理6个场分量的本征问题相比,大大降低了CPU时间,同时由给定的工作频率f求解相移常数β,易于实际应用.针对广义脊形传输器件的复杂结构,本文划分了不同的子区.几种代表性的脊形波导传输结构分析结果与其他方法一致,表明了本文分析思路的可行性.