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。     

一维弹道修正弹阻力环修正控制算法研究

根据一维弹道修正弹阻力环修正技术的特点,建立了一维弹道修正弹的弹道模型.在此基础上分析了利用阻力环进行一维弹道修正的能力以及阻力环张开时刻与射程修正量之间的关系.提出了阻力环张开时刻的算法.仿真结果表明,该算法具有较强的修正能力,选择合适的阻力环张开时刻,可以使弹丸的落点偏差大大减小.     

随机动态规划的混合算法研究

针对随机条件下动态规划模型的主要特点,运用智能算法混合编程理论,设计了一种探索多阶段决策问题的智能混合算法.该算法首先将问题转化成一族同类型的一步决策子问题,然后利用随机模拟和遗传算法,依据训练样本形成的训练神经元网络,在单步决策中寻求最优策略和最优目标值,逐个求解,再据初始状态逆序求出最优策略序列和最优目标值.仿真结果表明,该算法具有一定的通用性,初始设计点可以随机产生,其计算精度不因函数的非线性强弱而受影响,对目标和约束的限制较少,可应用于多种形式的随机多阶段决策优化问题,较好地满足了随机动态规划模型求解和优化的要求.     

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     

基于优化初始聚类中心K-Means算法的跳频信号分选

提出了一种优化初始聚类中心的方法.方法通过搜索参数统计直方图峰值预估类数目,并根据峰值位置确定聚类中心大概位置.由于优化的初始类心与实际类心相隔不远,聚类迭代次数大为减少.与传统的优化聚类中心方法相比,本方法计算量更少.最后将改进K-Means聚类算法应用于跳频信号分选,仿真结果表明,分选效果良好.     

高非线性度弹性S盒的构造

弹性S盒可应用于容错分布计算,量子密码密钥分配和流密码中伪随机序列产生.基于线性码和高非线性度的S盒,给出了一种构造具有高非线性度,且代数次数大于给定值的弹性S盒的方法.对于给定参数的线性码,构造的弹性S盒的非线性度是可以计算的.结果表明所构造的函数的非线性度优于已有的结果.     

Two‐machine flow shop scheduling with common due window to minimize weighted number of early and tardy jobs

This article studies two due window scheduling problems to minimize the weighted number of early and tardy jobs in a two‐machine flow shop, where the window size is externally determined. These new scheduling models have many practical applications in real life. However, results on these problems have rarely appeared in the literature because of a lack of structural and optimality properties for solving them. In this article, we derive several dominance properties and theorems, including elimination rules and sequencing rules based on Johnsos order, lower bounds on the penalty, and upper bounds on the window location, which help to significantly trim the search space for the problems. We further show that the problems are NP‐hard in the ordinary sense only. We finally develop efficient pseudopolynomial dynamic programming algorithms for solving the problems. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

What you should know about approximate dynamic programming

Approximate dynamic programming (ADP) is a broad umbrella for a modeling and algorithmic strategy for solving problems that are sometimes large and complex, and are usually (but not always) stochastic. It is most often presented as a method for overcoming the classic curse of dimensionality that is well‐known to plague the use of Bellman's equation. For many problems, there are actually up to three curses of dimensionality. But the richer message of approximate dynamic programming is learning what to learn, and how to learn it, to make better decisions over time. This article provides a brief review of approximate dynamic programming, without intending to be a complete tutorial. Instead, our goal is to provide a broader perspective of ADP and how it should be approached from the perspective of different problem classes. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

炮兵火力任务分配的优化模型

现代作战,参战兵种多,炮兵的火力单位和类型更为复杂,不同的火力单位具有不同的毁伤效果,如何用最小的代价取得最大的军事效益,是一种火力任务分配的优化问题.根据不同炮种和目标的特点,建立在一定约束条件下的炮兵火力任务分配模型,并将其转化为指派问题,运用匈牙利算法求解,达到优化分配火力任务的目的.通过仿真计算证明这是辅助指挥员进行射击决策的一种有效手段,为作战指挥理论提供了一种新的数学模型.     

基于多蚁群的无线传感器网络路由算法

无线传感器网络的快速发展,对于其路由协议有了更高的要求,关键是在节省能耗的情况下提高数据传输效率.提出了一种基于多蚁群无线传感器网络路由算法,采用多种群并行搜索,并在种群中采用基于目标函数值得启发式信息素分配策略和根据目标函数自动调整蚂蚁搜索路径,利用蚁群的分布式特点,通过有限寿命蚂蚁的协作在源节点与目的节点之间的运动获取主路径和备选路径,然后根据节点信息适时更新路由表.仿真结果显示MACRA降低了能耗,延长了网络寿命.