Algorithm to solve a chance‐constrained network capacity design problem with stochastic demands and finite support

We consider the problem of determining the capacity to assign to each arc in a given network, subject to uncertainty in the supply and/or demand of each node. This design problem underlies many real‐world applications, such as the design of power transmission and telecommunications networks. We first consider the case where a set of supply/demand scenarios are provided, and we must determine the minimum‐cost set of arc capacities such that a feasible flow exists for each scenario. We briefly review existing theoretical approaches to solving this problem and explore implementation strategies to reduce run times. With this as a foundation, our primary focus is on a chance‐constrained version of the problem in which α% of the scenarios must be feasible under the chosen capacity, where α is a user‐defined parameter and the specific scenarios to be satisfied are not predetermined. We describe an algorithm which utilizes a separation routine for identifying violated cut‐sets which can solve the problem to optimality, and we present computational results. We also present a novel greedy algorithm, our primary contribution, which can be used to solve for a high quality heuristic solution. We present computational analysis to evaluate the performance of our proposed approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 236–246, 2016     

Capacity expansion and cost efficiency improvement in the warehouse problem

The warehouse problem with deterministic production cost, selling prices, and demand was introduced in the 1950s and there is a renewed interest recently due to its applications in energy storage and arbitrage. In this paper, we consider two extensions of the warehouse problem and develop efficient computational algorithms for finding their optimal solutions. First, we consider a model where the firm can invest in capacity expansion projects for the warehouse while simultaneously making production and sales decisions in each period. We show that this problem can be solved with a computational complexity that is linear in the product of the length of the planning horizon and the number of capacity expansion projects. We then consider a problem in which the firm can invest to improve production cost efficiency while simultaneously making production and sales decisions in each period. The resulting optimization problem is non‐convex with integer decision variables. We show that, under some mild conditions on the cost data, the problem can be solved in linear computational time. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 367–373, 2016     

微纳卫星姿态确定与控制半实物仿真系统设计

航天器姿态控制系统需要特殊的运行环境,在地面很难考核,这给系统可靠性带来一定的风险。针对微纳卫星的特点,设计并研制了一套面向微纳卫星的姿态确定与控制半实物仿真系统。该系统通过数字化模型模拟卫星姿态轨道运动、敏感器模型产生敏感器测量数据、执行器模型生成控制力矩、敏感器模拟器实现通信协议,最终实现姿态控制系统的全系统仿真。这套系统可以接入卫星控制系统回路,实现对姿控系统软件、硬件的考核,同时验证算法的性能。基于该系统,对天拓三号卫星姿控系统进行地面半实物仿真,并对比在轨试验数据,结果表明系统设计合理,仿真结果可信。     

某型坦克对钢筋混凝土工事的射击效能分析

依据弹丸侵彻深度、毁伤概率、命中概率数学模型 ,结合敌海岸防御工事的特点 ,分析了某型坦克炮各种弹种的射击效能 ,计算了坦克在海上射击时对各种目标和工事的命中概率和毁伤概率 ,作出了在不同射击距离上选择不同弹种进行射击的结论。