Optimal patrol to uncover threats in time when detection is imperfect

Consider a patrol problem, where a patroller traverses a graph through edges to detect potential attacks at nodes. An attack takes a random amount of time to complete. The patroller takes one time unit to move to and inspect an adjacent node, and will detect an ongoing attack with some probability. If an attack completes before it is detected, a cost is incurred. The attack time distribution, the cost due to a successful attack, and the detection probability all depend on the attack node. The patroller seeks a patrol policy that minimizes the expected cost incurred when, and if, an attack eventually happens. We consider two cases. A random attacker chooses where to attack according to predetermined probabilities, while a strategic attacker chooses where to attack to incur the maximal expected cost. In each case, computing the optimal solution, although possible, quickly becomes intractable for problems of practical sizes. Our main contribution is to develop efficient index policies—based on Lagrangian relaxation methodology, and also on approximate dynamic programming—which typically achieve within 1% of optimality with computation time orders of magnitude less than what is required to compute the optimal policy for problems of practical sizes. © 2014 Wiley Periodicals, Inc. Naval Research Logistics, 61: 557–576, 2014     

具有适应值预测机制的遗传算法

针对适应值计算费时的优化问题,提出一种具有适应值预测机制的遗传算法:为了有效控制预测适应值的准确度和预测频率,建立了一个基于可信度概念的适应值预测模型,引入可信度流失机制以减少预测误差的传播和累积,引入冗余个体剔除机制以减少计算消耗。利用3个基准函数对算法进行收敛性和有效性的测试,测试结果表明算法对于3个测试函数均能获得满意的最优解,并且都能减少60%以上的真实适应值计算次数。     

基于遗传算法的嵌入式软件测试用例生成系统研究

综合考虑了嵌入式软件的特点，将遗传算法应用于搜索全面覆盖软件特殊路径的测试用例生成的问题，合理构建了嵌入式软件测试用例自动生成系统，给出了系统流程图，改进了部分算子，使搜索效果得以加强，并分析了交叉率、变异率等参数的取值范围，通过改变不同的参数值得到对比图，以确定适合该系统的最佳参数值，并针对实际汇编语言编写的嵌入式软件指定路径进行仿真测试，从理论和实践上证明了该思路的正确性和可行性。     

经马氏修正的Poisson过程的极大似然估计

近年来 ,隐马氏模型成为研究相依随机变量的一个十分有用的工具。实际应用过程中的一个很重要的问题是如何对隐马氏模型的参数进行估计。将一类连续时间隐马氏模型的问题转化为离散时间隐马氏模型的问题 ,给出了具体的隐马氏模型———经马氏修正的Poisson过程的极大似然估计及其算法。此类过程被广泛用来对复杂电信网络的交通流进行建模     

基于风险控制的装备供应链网络设计模型

针对风险管理中的装备供应链正向（供应）网络设计问题，在对装备供应链风险和成本进行量化分析的基础上，综合考虑风险和成本2方面因素，建立了基于风险控制的装备供应链网络设计优化模型。并设计了遗传算法对模型进行求解，给出在指定风险水平下最优设计方案与总成本。最后通过实例分析和计算，结果表明，该优化模型合理、有效、可行。     

任意同轴圆线圈互感系数的近似解析公式

为使任意大小、任意距离的两同轴圆线圈之间的互感系数能用关系简单明了的常用解析函数表示,先对用毕奥-萨伐尔定律导出的互感系数积分公式进行数值计算,然后通过对极端情况的分析和对非极端情况进行猜想,采用幂级数、指数、对数或其组合进行试探,再用数值计算验证,最终尝试性地分6种情形给出了两同轴圆线圈在任意大小、任意距离下（除两线圈几乎重合外）互感系数的近似解析表达式。函数表达式比较简单,物理意义比较明确,且相对误差在±5%以内。     

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

基于预配装思想的物资混装配载优化策略

提出了一种基于预配载思想的装备物资混装配载策略,并应用模糊聚类和混合智能算法进行了实例仿真。研究对于组合优化策略在装备保障信息化系统建设中的应用具有积极意义。     

Efficient sequential decision‐making algorithms for container inspection operations

Following work of Stroud and Saeger (Proceedings of ISI, Springer Verlag, New York, 2006) and Anand et al. (Proceedings of Computer, Communication and Control Technologies, 2003), we formulate a port of entry inspection sequencing task as a problem of finding an optimal binary decision tree for an appropriate Boolean decision function. We report on new algorithms for finding such optimal trees that are more efficient computationally than those presented by Stroud and Saeger and Anand et al. We achieve these efficiencies through a combination of specific numerical methods for finding optimal thresholds for sensor functions and two novel binary decision tree search algorithms that operate on a space of potentially acceptable binary decision trees. The improvements enable us to analyze substantially larger applications than was previously possible. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

基于遗传算法的战时维修保障系统优化研究

分析了战时维修保障系统的结构功能,给出了维修保障系统的解析模型,提出了维修保障系统的可控参数及指标;为了使维修保障系统发挥最佳效能,以最小二乘准则作为系统的优化准则,建立了维修保障系统的优化模型,采用遗传算法对优化模型进行求解,给出了计算方法,并以计算实例验证了方法的可行性。