The knapsack problem with a minimum filling constraint

We study a knapsack problem with an additional minimum filling constraint, such that the total weight of selected items cannot be less than a given threshold. The problem has several applications in shipping, e‐commerce, and transportation service procurement. When the threshold equals the knapsack capacity, even finding a feasible solution to the problem is NP‐hard. Therefore, we consider the case when the ratio α of threshold to capacity is less than 1. For this case, we develop an approximation scheme that returns a feasible solution with a total profit not less than (1 ‐ ε) times the total profit of an optimal solution for any ε > 0, and with a running time polynomial in the number of items, 1/ε, and 1/(1‐α). © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

A branch‐and‐bound‐based solution approach for dynamic rerouting of airborne platforms

This article is a sequel to a recent article that appeared in this journal, “An extensible modeling framework for dynamic reassignment and rerouting in cooperative airborne operations” [ 17 ], in which an integer programming formulation to the problem of rescheduling in‐flight assets due to changes in battlespace conditions was presented. The purpose of this article is to present an improved branch‐and‐bound procedure to solve the dynamic resource management problem in a timely fashion, as in‐flight assets must be quickly re‐tasked to respond to the changing environment. To facilitate the rapid generation of attractive updated mission plans, this procedure uses a technique for reducing the solution space, supports branching on multiple decision variables simultaneously, incorporates additional valid cuts to strengthen the minimal network constraints of the original mathematical model, and includes improved objective function bounds. An extensive numerical analysis indicates that the proposed approach significantly outperforms traditional branch‐and‐bound methodologies and is capable of providing improved feasible solutions in a limited time. Although inspired by the dynamic resource management problem in particular, this approach promises to be an effective tool for solving other general types of vehicle routing problems. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Bounded flexibility in days‐on and days‐off scheduling

This article presents a flexible days‐on and days‐off scheduling problem and develops an exact branch and price (B&P) algorithm to find solutions. The main objective is to minimize the size of the total workforce required to cover time‐varying demand over a planning horizon that may extend up to 12 weeks. A new aspect of the problem is the general restriction that the number of consecutive days on and the number of consecutive days off must each fall within a predefined range. Moreover, the total assignment of working days in the planning horizon cannot exceed some maximum value. In the B&P framework, the master problem is stated as a set covering‐type problem whose columns are generated iteratively by solving one of three different subproblems. The first is an implicit model, the second is a resource constrained shortest path problem, and the third is a dynamic program. Computational experiments using both real‐word and randomly generated data show that workforce reductions up to 66% are possible with highly flexible days‐on and days‐off patterns. When evaluating the performance of the three subproblems, it was found that each yielded equivalent solutions but the dynamic program proved to be significantly more efficient. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 678–701, 2013     

载体干扰磁场补偿方法

获得载体航行路径上各点地磁场的精确测量值是地磁匹配导航的前提,而载体上各种干扰磁场的存在会引起磁力仪输出的偏差,影响匹配的精度,因此必须对载体干扰磁场进行补偿。在分析载体干扰磁场特性的基础上,提出利用矢量测量值对地磁场总场值进行补偿的方法。该方法首先根据矢量磁力仪的测量模型得到关于载体磁场参数的非线性方程,然后采用非线性参数估计方法估计出精确的载体干扰磁场系数,最后再利用估计结果对测量值进行补偿。通过仿真对该方法的有效性进行研究,并设计了半实物实验对其实用性进行验证。结果表明采用本文提出的方法补偿后地磁场总场值的测量误差在20nT以内,而且该方法参数估计精度高,应用方便,可以有效地对导航载体干扰磁场进行补偿。     

高超声速飞行器俯冲机动最优制导方法

为解决高超声速飞行器俯冲段精确制导与机动突防问题,研究了机动突防最优制导方法。针对零化视线角速率降低突防性能的问题,在俯冲平面及转弯平面内分别设计了正弦形式的视线角参考运动,同时为进一步实现俯冲精确制导,以落速最大为性能指标利用最优控制对其进行跟踪,引入了伪控制量以简化最优制导问题的求解,最后分析了该方法的稳定性及制导性能。以CAV-H为例进行仿真分析,仿真结果表明该方法能够实现机动飞行,且能够高精度地满足终端落角及落点约束,可为高超声速飞行器俯冲段精确制导及机动突防提供参考。     

水下航行器燃烧室两相流燃烧数值模拟

提出水下航行器燃烧室中两相流燃烧数值模拟方法.采用k-ε双方程湍流模型、涡耗散燃烧模型、离散相液滴模型进行数值模拟,得到单组元推进剂燃烧的速度场、温度场、浓度场的分布.研究了喷嘴压差、环境背压对燃烧的影响,得出了一定范围内,增大喷嘴压差、增大环境背压可以增强燃烧效果的结论.     

PHEV电池电荷状态估计设计及仿真

电池管理系统(battery management system,BMS)是混合动力汽车(parallel hybrid electric vehicle,PHEV)能量管理系统中的核心组成部分,而其中电池电荷状态(state of charge,soc)则是PHEV控制策略中的重要参数.针对PHEV动力电池组SOC系统高度非线性和复杂性的特点,提出了一种基于改进的BP神经网络的HEV动力电池组的实时SOC估计,并对网络的收敛性进行了证明.利用大量PHEV动力电池组在行驶过程中充放电的数据样本,对神经网络进行网络训练并且进行仿真.结果表明,与传统离线SOC估计方法相比,能够有效地减小误差,提高电池SOC的精度.     

飞行操作任务的无人机模拟训练及系统设计

为了提高无人机模拟训练的逼真度和沉浸感.研究了无人机飞行操作训练的关键技术,以半实装的形式构建了模拟飞行训练系统的体系结构.通过对飞行操作训练关键技术的研究和飞行操作模拟训练系统的设计,可以对基层部队的无人机地面操控手高逼真模拟训练提供理论基础和系统支持.     

需求可拆分的应急物资调度问题的蚁群算法

应急物资调度问题是个典型的需求可拆分的车辆路径问题,区别于传统的车辆路径问题,将每个需求节点只能由一辆车访问的约束去除,允许需求节点由多辆车进行访问。针对应急物资调度问题的特点,建立相应的多目标车辆路径数学规划模型(SDVRP),并根据模型特点设计改进蚁群优化算法。最后,进行相应的算例分析,验证了该模型和算法的有效性。     

瓶颈指派问题的一种多项式时间算法

本文对瓶颈指派问题给出了一种新的算法,该算法不需要利用最大流算法,而类似于解经典指派问题的匈牙利算法。该算法是一个多项式时间算法,其复杂性为Ｏ（ｎ３）