一种运用遗传算法确定船舶航向控制模糊规则的方法

为了克服船舶航向控制模糊规则确定过程中的盲目性,引入一种与之相适应的遗传算法,以使结果成为某种意义下的最优解,从而从根本上解决这一重要问题.文中运用Matlab的C语言MEX-文件技术,将遗传算法源代码与Matlab直接结合起来,利用后者的强大建模能力,建立起完整的仿真模型.仿真结果表明,船舶的航向控制能力得到明显改善.     

An integer decomposition algorithm for solving a two‐stage facility location problem with second‐stage activation costs

We study a stochastic scenario‐based facility location problem arising in situations when facilities must first be located, then activated in a particular scenario before they can be used to satisfy scenario demands. Unlike typical facility location problems, fixed charges arise in the initial location of the facilities, and then in the activation of located facilities. The first‐stage variables in our problem are the traditional binary facility‐location variables, whereas the second‐stage variables involve a mix of binary facility‐activation variables and continuous flow variables. Benders decomposition is not applicable for these problems due to the presence of the second‐stage integer activation variables. Instead, we derive cutting planes tailored to the problem under investigation from recourse solution data. These cutting planes are derived by solving a series of specialized shortest path problems based on a modified residual graph from the recourse solution, and are tighter than the general cuts established by Laporte and Louveaux for two‐stage binary programming problems. We demonstrate the computational efficacy of our approach on a variety of randomly generated test problems. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

一类线性规划模型的求解方法

应用矩阵理论知识得到了一类特殊的线性规划模型的相关定理,给出了一种简便求解方法,讨论了求解方法的推广问题.     

基于双层规划的通信干扰兵力部署优化

投掷式通信干扰机是未来通信对抗装备发展的一种趋势,针对其压制无线战术通信的兵力部署优化问题,引入"通信干扰压制概率"和"通信干扰效益"两个指标,建立了基于双层规划的兵力部署优化模型,上层规划以整体通信干扰效益最大化为目标,下层为随机机会约束规划,以通信干扰压制概率满足一定置信水平为约束,以干扰机需求量最小化为目标。采用随机模拟、遗传算法和动态规划相结合的混合智能算法求解双层规划模型,并通过算例分析验证了模型的有效性。     

基于组合权重的目标识别系统威胁评估

现代信息战场中,对敌方的目标识别系统进行有效干扰,是增强我方、打击敌方的有效手段。对敌方的目标识别系统进行有效的威胁评估,有助于指挥员的决策以及对干扰资源的优化配置。借鉴空中目标威胁评估常用方法,提出对敌方目标的敌我属性识别系统进行威胁评估的方法。首先选择合理的威胁评估指标,然后对指标数据进行规范化处理,利用信息熵法求解威胁评估的客观权重与改进的层次分析法求解出的主观权重加权得到组合权重,运用灰关联分析法进行威胁评估和排序,最后用实例验证方法的有效性和合理性。     

A generic model of motor‐carrier fuel optimization

Fuel optimizers are decision models (software products) that are increasingly recognized as effective fuel management tools by U.S. truckload carriers. Using the latest price data of every truck stop, these models calculate the optimal fueling schedule for each route that indicates: (i) which truck stop(s) to use, and (ii) how much fuel to buy at the chosen truck stop(s) to minimize the refueling cost. In the current form, however, these models minimize only the fuel cost, and ignore or underestimate other costs that are affected by the models' decision variables. On the basis of the interviews with carrier managers, truck drivers, and fuel‐optimizer vendors, this article proposes a comprehensive model of motor‐carrier fuel optimization that considers all of the costs that are affected by the model's decision variables. Simulation results imply that the proposed model not only attains lower vehicle operating costs than the commercial fuel optimizers, but also gives solutions that are more desirable from the drivers' viewpoint. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

数据库安全管理及访问控制中问件的设计与实现

为确保军事敏感数据安全，在全面分析和研究数据库安全漏洞、安全策略、安全目标的基础上，提出了利用中间件技术实现客户访问数据库控制机制。针对两类操作系统的客户端，设计实现了通信控制中间件，使具有授权的用户通过中间层认证辨识后才能正确地访问数据库，确保了数据库信息安全。     

On efficient algorithms for finding efficient salvo policies

We consider the salvo policy problem, in which there are k moments, called salvos, at which we can fire multiple missiles simultaneously at an incoming object. Each salvo is characterized by a probability p_i: the hit probability of a single missile. After each salvo, we can assess whether the incoming object is still active. If it is, we fire the missiles assigned to the next salvo. In the salvo policy problem, the goal is to assign at most n missiles to salvos in order to minimize the expected number of missiles used. We consider three problem versions. In Gould's version, we have to assign all n missiles to salvos. In the Big Bomb version, a cost of B is incurred when all salvo's are unsuccessful. Finally, we consider the Quota version in which the kill probability should exceed some quota Q. We discuss the computational complexity and the approximability of these problem versions. In particular, we show that Gould's version and the Big Bomb version admit pseudopolynomial time exact algorithms and fully polynomial time approximation schemes. We also present an iterative approximation algorithm for the Quota version, and show that a related problem is NP-complete.     

A multi‐stage stochastic programming approach for network capacity expansion with multiple sources of capacity

In networks, there are often more than one sources of capacity. The capacities can be permanently or temporarily owned by the decision maker. Depending on the nature of sources, we identify the permanent capacity, spot market capacity, and contract capacity. We use a scenario tree to model the uncertainty, and build a multi‐stage stochastic integer program that can incorporate multiple sources and multiple types of capacities in a general network. We propose two solution methodologies for the problem. Firstly, we design an asymptotically convergent approximation algorithm. Secondly, we design a cutting plane algorithm based on Benders decomposition to find tight bounds for the problem. The numerical experiments show superb performance of the proposed algorithms compared with commercial software. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 600–614, 2017