目标搜索的预测分析及搜索计划的优化逼近

给出了目标搜索的预测分析公式,提出了最优搜索计划的一种优化逼近方法及有关实例     

一种无约束最优化方法——恰当共轭方向法

本文提出了一种求解无约束最优化问题的方法,称之为“恰当共轭方向法”。与通常的共轭方向法(如共轭梯度法)相比,这种方法可以节省大量的一维搜索工作量,并且还能提高收敛速率。     

To catch an intruder: Part A—uncluttered scenario

We analyze an interdiction scenario where an interceptor attempts to catch an intruder as the intruder moves through the area of interest. A motivating example is the detection and interdiction of drug smuggling vessels in the Eastern Pacific and Caribbean. We study two models in this article. The first considers a nonstrategic target that moves through the area without taking evasive action to avoid the interdictor. We determine the optimal location the interceptor should position itself to best respond when a target arrives. The second model analyzes the strategic interaction between the interceptor and intruder using a Blotto approach. The intruder chooses a route to travel on and the interceptor chooses a route to patrol. We model the interaction as a two‐player game with a bilinear payoff function. We compute the optimal strategy for both players and examine several extensions. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 29–40, 2017     

Cyclic best first search: Using contours to guide branch‐and‐bound algorithms

The cyclic best‐first search (CBFS) strategy is a recent search strategy that has been successfully applied to branch‐and‐bound algorithms in a number of different settings. CBFS is a modification of best‐first search (BFS) that places search tree subproblems into contours which are collections of subproblems grouped in some way, and repeatedly cycles through all non‐empty contours, selecting one subproblem to explore from each. In this article, the theoretical properties of CBFS are analyzed for the first time. CBFS is proved to be a generalization of all other search strategies by using a contour definition that explores the same sequence of subproblems as any other search strategy. Further, a bound is proved between the number of subproblems explored by BFS and the number of children generated by CBFS, given a fixed branching strategy and set of pruning rules. Finally, a discussion of heuristic contour‐labeling functions is provided, and proof‐of‐concept computational results for mixed‐integer programming problems from the MIPLIB 2010 database are shown. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 64–82, 2017     

具有空间坐标耦合的二阶集群模型分析

在空间坐标耦合的情形下建立一种改进的二阶分布式集群模型。分析结果显示,如果系统的拓扑结构不变,当其确定的有向图具有有向支撑树并且速度的伴随系数大于某一临界值时,整个群体将随着耦合矩阵的旋转角的变化而呈现出三种集群样式——直线模式、圆柱螺线模式以及对数螺线模式。最后给出了这三种样式所对应的数值仿真结果。     

多机吊放声纳对潜警戒扇面动态计算方法

针对多架反潜直升机使用吊放声纳搜索时的对潜警戒扇面动态计算问题,根据搜索方法建立多机悬停点坐标解算模型;采用等效的方法,将当前悬停点吊放声纳的探测区域与所有已完成探测的悬停点不存在潜艇的区域等效为对潜警戒范围进行计算;建立了各悬停点探测区域相对舰艇编队舷角的动态计算模型;给出了动态计算多机对潜警戒扇面起始、终止舷角的计算方法。最后仿真计算了对潜警戒扇面随搜索时间、间距系数的动态变化关系。结果显示:对潜警戒扇面将在一定范围内周期性动态变化;且受间距系数的影响较大。     

程序进化器

研究用模拟进化方法进行程序设计的途径。构造了以形式文法为遗传表示的程序进化器,提出了这个进化器使用的有关算法。本文用程序进化器解决了人工蚁问题。     

反潜直升机吊声搜潜效能的建模仿真

从直升机使用吊放声纳(简称吊声)的搜潜过程入手,通过仿真环境假设,吊声搜潜效能描述,建立了吊声搜潜效能的蒙特卡洛法模型。介绍了常用搜索方法,并建立了其搜索要素表。根据模型编制了仿真程序,实现了不同搜索方法的仿真计算,为研究不同战术条件下如何合理选择有效的搜索方法奠定了基础。     

舰载直升机反潜搜索最佳方案优选模型及应用

目前,舰载直升机已成为现代水面舰艇搜潜反潜的重要力量,为了提高作战效率,对舰载直升机在反潜搜索中的战斗使用进行了研究,建立了搜索力的最优配置模型,解决了在已知目标分布的条件下舰载直升机反潜搜索中选择初始探测点、确定搜索路径、确定搜索次数以及搜索效率评估等问题,并在几种常见的目标分布下对最佳搜索方案作了实例演示,为舰载直升机的反潜战斗使用提供了依据。     

A search game with a protector

A classic problem in Search Theory is one in which a searcher allocates resources to the points of the integer interval [1, n] in an attempt to find an object which has been hidden in them using a known probability function. In this paper we consider a modification of this problem in which there is a protector who can also allocate resources to the points; allocating these resources makes it more difficult for the searcher to find an object. We model the situation as a two‐person non‐zero‐sum game so that we can take into account the fact that using resources can be costly. It is shown that this game has a unique Nash equilibrium when the searcher's probability of finding an object located at point i is of the form (1 − exp (−λ_ix_i)) exp (−μ_iy_i) when the searcher and protector allocate resources x_i and y_i respectively to point i. An algorithm to find this Nash equilibrium is given. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47:85–96, 2000