最小费用树

本文在赋边权w和顶点权θ的网络中,建立了最小费用树问题的网络模型。文中对问题的复杂性进行了讨论并给出了求解问题的算法     

BP神经网络的飞机机体研制费用估算

提出一种应用人工神经网络预测飞机机体研制费用的方法.该方法利用偏最小二乘法对飞机性能参数进行了主成分提取,用这些主成分作为BP网络的输入变量,建立了一种基于BP神经网络的飞机研制费用的估算模型,应用该模型对典型的飞机机体研制费用进行了预测.预测结果表明,该方法是有效的、可行的.     

武器系统模糊寿命周期费用模型

武器系统的寿命周期费用建模较多采用参数法,而参数法中最常用的是最小二乘回归.考虑费用统计数据的模糊性,提出用模糊最小二乘回归来建立武器系统模糊寿命周期费用模型,并结合实例对武器系统寿命周期费用进行了分析.结果表明,这种方法能达到令人满意的拟合精度,具有实用价值.     

Optimal control policies for an inventory system with commitment lead time

We consider a firm which faces a Poisson customer demand and uses a base‐stock policy to replenish its inventories from an outside supplier with a fixed lead time. The firm can use a preorder strategy which allows the customers to place their orders before their actual need. The time from a customer's order until the date a product is actually needed is called commitment lead time. The firm pays a commitment cost which is strictly increasing and convex in the length of the commitment lead time. For such a system, we prove the optimality of bang‐bang and all‐or‐nothing policies for the commitment lead time and the base‐stock policy, respectively. We study the case where the commitment cost is linear in the length of the commitment lead time in detail. We show that there exists a unit commitment cost threshold which dictates the optimality of either a buy‐to‐order (BTO) or a buy‐to‐stock strategy. The unit commitment cost threshold is increasing in the unit holding and backordering costs and decreasing in the mean lead time demand. We determine the conditions on the unit commitment cost for profitability of the BTO strategy and study the case with a compound Poisson customer demand.     

基于博弈论的装备科研、购置、维修经费比例关系优化分析

通过不同时期国家战略部署、科研发展情况及经济承受能力对装备经费分配的影响分析,采用博弈的方法,建立了装备科研、购置和维修费之间的比例关系优化模型,给出了寻求纳什均衡点的迭代算法,并进行了仿真计算.仿真结果证明了该方法的可行性与正确性.     

基于事例推理的装备软件成本估算研究

采用基于事例推理的估算方法可以很好地解决传统经验函数估算软件成本时的局限性。讨论了装备软件成本估算和基于事例推理研究的特点,从总体上描述了基于事例推理装备软件成本估算系统结构和实现流程,阐述了主要的研究内容,包括影响软件成本因素、系统的事例表示方法以及相似度的基本算法及事例的改写,并通过实例验证了事例推理在装备软件成本估算实践中的具体应用。     

基于模糊动态层次分析法的军车全寿命费用模型

为研究军车最优的效费比,提出了控制军车装备费用增长的有效途径——全寿命费用管理方法,并通过模糊动态层次分析法建立了分析决策模型,将定性与定量的分析有机结合起来研究军车全寿命费用的变化趋势,有利于提高军车装备的可靠性和决策的科学性,具有较好的应用价值。     

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     

基于循环子空间理论的线性系统测试矩阵优化

研究了线性定常系统在循环指数大于1(即其约当标准形不同的约当块有重根)的情况下测试矩阵的优化方法.以循环子空间相关定理的证明为基础,根据根向量链的相关特性,得到了测试向量的线性和与系统观测性的直接关系,给出了在保证系统可观测性的同时,使得测试代价最小的测试矩阵优化方法.算例表明,提出的方法简单直观,对配置测试向量具有良好的工程价值.     

具有全局收敛性的盲均衡算法

为了解决传统的自适应均衡技术需发送训练序列的问题,采用盲均衡技术,利用接收信号本身的特征使均衡器收敛。提出了一种新的盲均衡算法(C&D算法),该算法将CRIMNO算法和判决引导(Decision Directed,DD)算法相结合,利用信号序列间的互不相关特性,从而使其具有全局收敛性能。实验结果表明:与CRIMNO算法相比,在相同的信噪比下,该算法具有收敛快速、运算量少和残留误差小的特点。