战役炮兵火力毁伤筹划中“直接计算法”的应用

我军兼收俄、美火力毁伤理论之优长,依据我军编制体制、武器装备和作战原则,运用科学的数据和算法,创建了具有我军特色的战役炮兵火力毁伤理论。基于直接计算的目标选择方法,分别对直接计算目标选择方法的基本思路、主要优点和实施过程进行了论述。该计算方法较好地解决了针对具体目标如何进行兵器弹药需求量计算的问题,使战役炮兵火力毁伤筹划方法更具科学性。     

重大活动安全警卫工作之我见

当前,重要会议、重大活动已经成为群众上访制造事端扩大影响的首选目标。同时,也成为敌对分子、恐怖组织企图实施阴谋暗害和恐怖破坏活动的主要选择场所。为防止上述事件发生,警卫部队要处理好三种关系,掌握情报信息。严密部署。     

城乡一体化发展模式下的消防规划编制问题研究

消防规划的编制和实施,作为城市公共安全的一项基础工程,如何科学的地融入城乡一体化发展进程,是新形势下筑牢城乡火灾预防体系物质基础的关键。分析了城乡一体化背景下城市消防规划建设存在的问题和福建省当前消防规划编制情况,提出了城乡一体化发展模式下编制消防规划应掌握的环节。     

威胁联网下低空突防航路规划研究

分析了威胁联网下信息交流和资源共享对飞行航路规划的影响;针对威胁联网,制定相关的威胁体相互支援表,采用遗传算法进行低空突防航路规划.通过仿真计算证明,此方法规划出的飞行航路能有效提高威胁联网下的战斗机低空突防安全性,为航路规划提供了一种新思路.     

基于混合算法的局部路径规划

人工势场法是一种常用的具有算法简单和便于实时控制的局部路径规划方法,但存在容易产生局部极小值的问题。基于模糊逻辑的局部路径规划法具有环境适应性强等优点,它在连续论域内采用模糊路径规划时,计算量比较大。提出了一种将人工势场法和模糊逻辑法相结合进行局部路径规划的混合算法。具体方法是在一般情况下采用人工势场法进行局部路径规划,当产生局部极小值时,采用模糊逻辑法进行局部路径规划。仿真结果表明,该方法能有效地解决局部极小值问题,给智能车规划出光滑的路径。     

基于改进遗传算法的反舰导弹航路规划模型研究

针对传统遗传算法在进行复杂的大范围优化问题时容易陷入局部最优和收敛速度慢的局限,提出采用基于混沌的遗传算法进行反舰导弹航路优化问题的求解。在遗传算法操作时加入混沌操作,扩大了搜索范围,提高了优化速度,有效地解决了解空间巨大带来遗传算法的上述局限性。     

基于水下声场信息的三维航路规划研究

针对目前大规模水下复杂战场环境中的航路规划困难的问题。设计了一种以距离值传递法为基础的航路规划方法,该方法以水下声场为主要威胁源,运用三维抛物方程(PE)模型计算水下声场数据,并以此建立三维水下战场环境。利用限制线性八叉树的方法对数据场进行数据分割,从而达到对搜索空间的压缩,最后通过距离值传递法搜索得到最佳航路。仿真结果表明该方法较快的实现了三维声场环境下的不同起始点、多目标寻径,满足一定条件下航路规划要求。     

基于 ANP 的作战筹划能力模糊评价方法

基于网络层次分析（ANP）的模糊评价方法,通过对作战筹划能力进行分析评价,为提升作战筹划能力提供参考。首先运用 ANP 法,提出包含4个方面18个指标的评估指标体系,构建作战筹划能力评估模型,然后通过模糊综合评价法对作战筹划能力进行评价。该评估模型探索了筹划能力评价的方法,为作战筹划能力评价工作提供新思路。     

Level workforce planning for multistage transfer lines

In this article, we define two different workforce leveling objectives for serial transfer lines. Each job is to be processed on each transfer station for c time periods (e.g., hours). We assume that the number of workers needed to complete each operation of a job in precisely c periods is given. Jobs transfer forward synchronously after every production cycle (i.e., c periods). We study two leveling objectives: maximin workforce size () and min range (R). Leveling objectives produce schedules where the cumulative number of workers needed in all stations of a transfer line does not experience dramatic changes from one production cycle to the next. For and a two‐station system, we develop a fast polynomial algorithm. The range problem is known to be NP‐complete. For the two‐station system, we develop a very fast optimal algorithm that uses a tight lower bound and an efficient procedure for finding complementary Hamiltonian cycles in bipartite graphs. Via a computational experiment, we demonstrate that range schedules are superior because not only do they limit the workforce fluctuations from one production cycle to the next, but they also do so with a minor increase in the total workforce size. We extend our results to the m‐station system and develop heuristic algorithms. We find that these heuristics work poorly for min range (R), which indicates that special structural properties of the m‐station problem need to be identified before we can develop efficient algorithms. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 577–590, 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