随机搜索与最优搜索

本文提出了由最优搜索向局部最优随机搜索转化的一种设想 ,对转化过程的实现、搜索力的确定、各种情况下搜索发现目标的概率等进行了论证和比较 ,并对由此而涉及的增量搜索问题也作了相应的研究。     

最优搜索力的确定及增量搜索计划

当静止目标位置服从圆正态分布时,提出了在一定的期望搜索效果前提下确定需参加搜索的最优搜索兵力的求算方法,导出了在首轮搜索未果时追加搜索力进行后续搜索的最优增量搜索计划,并且证明了最优总量搜索(即一次性搜索)与最优增量搜索效率相等的重要结论。     

UUV编队协同搜索静止目标的准最优方法

考虑到操作的简单性且实际执行搜索任务时搜索力不是无限可分,将连续空间的搜索问题转换为离散空间的最优搜索问题。通过划分网格,将连续的目标位置分布离散化。根据最优搜索理论,提出了单个无人水下航行器的准最优随机搜索方法,较好地逼近理论最优值。并以此为基础,分析了无人水下航行器编队的3种协同搜索方法:集中最优搜索、分散最大概率搜索和准最优搜索。最后通过实例仿真,得出了编队准最优搜索策略的有效性、优越性和可操作性。此方法将对无人水下航行器编队的战法研究具有参考借鉴意义。     

离散搜索力的最优配置模型及增量搜索计划

目前,离散搜索正越来越普遍地应用于各种搜索实践。为了优化搜索过程,提高离散搜索的效率,应用最优搜索理论,导出了待搜目标服从均匀分布、正态分布时离散搜索力的最优配置模型、目标的踪迹预测方法和最优增量搜索计划的求法,并通过实例作了演示,上述结论和方法为离散搜索力如何实施最优搜索提供了一定的理论依据。     

舰艇CGF搜潜过程马氏决策规划模型

舰艇搜索潜艇的过程可以近似地看作一种马尔可夫过程.研究了潜艇训练仿真系统中舰艇CGF(计算机生成兵力)搜索潜艇过程中的状态转移过程和随机搜索发现目标的概率模型,将舰艇CGF搜索潜艇的过程分为若干独立的阶段,建立了搜潜过程马氏决策规划模型,提出了在各种不同初始搜索状态下的舰艇搜索策略.仿真结果给出了舰艇CGF的最优搜索策略集合和发现概率,验证了马氏决策规划模型的有效性.     

潜艇离散搜索分析

以潜艇离散搜索战术为背景,对离散搜索的定义及优缺点进行了阐述,建立了离散搜索发现概率模型,模型中对单位周期的发现目标期望数和发现概率进行了计算,并对隐蔽与非隐蔽两种离散搜索样式的搜索效果进行了模拟仿真,但计算中没有考虑水声环境的影响和敌方潜艇实施反搜索的情况,最后,结合仿真结果,针对潜艇实际运用确定了高低速航行时间,提出了实施此战术时的几点建议,以期为部队合理使用离散搜索战术提供决策依据。     

航空搜救范围与成功概率研究

从遇险对象分布情况和理想发现概率分析入手,对影响航空搜索的修正因素、扫视宽度以及可搜索范围进行了解读,全面梳理了实际发现概率、成功概率、包含概率和累积成功概率,为航空搜救行动中搜救范围的确定以及搜索成功概率的分析提供了有效手段和支撑。     

攻击机对地面目标目视搜索效能模型

攻击机对地面目标目视搜索效能是作战效能评估的基础,建立攻击机对地面目标目视搜索效能数学模型,并分析搜索方法对目标发现概率的影响,以及不同目标搜索条件下目标搜索方法的优选,以提高目标发现概率,进而提高攻击机的作战效能.同时,为作战人员根据不同目标搜索条件,选取较优的目标搜索方法提供理论依据.     

一种新的对潜应召搜索法及其效能分析

论述了一种新的对潜应召搜索法 ,并对其效能进行了分析 ,同时就平均发现概率、搜索时间、转向次数三个指标与海军现在使用的扩展方阵搜索法进行了仿真比较     

随机运动目标区域持续探测的概率最优性

研究了随机运动目标有限区域持续探测的概率最优性问题,证明了区域一次探测概率随时间递减。建立了相邻探测点累计发现概率与一个探测点探测周期数的数学关系,并给出了一个计算探测最大概率周期数的判据,应用此判据,可以搜索获得最优探测周期数。进行了直升机吊放声纳持续探测发现概率最优性仿真,仿真表明了计算的有效性,并得出了应以最小周期数进行直升机吊放声纳探测的结论。     

Discrete search allocation game with false contacts

This paper deals with a two‐person zero‐sum game called a search allocation game, where a searcher and a target participate, taking account of false contacts. The searcher distributes his search effort in a search space in order to detect the target. On the other hand, the target moves to avoid the searcher. As a payoff of the game, we take the cumulative amount of search effort weighted by the target distribution, which can be derived as an approximation of the detection probability of the target. The searcher's strategy is a plan of distributing search effort and the target's is a movement represented by a path or transition probability across the search space. In the search, there are false contacts caused by environmental noises, signal processing noises, or real objects resembling true targets. If they happen, the searcher must take some time for their investigation, which interrupts the search for a while. There have been few researches dealing with search games with false contacts. In this paper, we formulate the game into a mathematical programming problem to obtain its equilibrium point. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

A search game taking account of attributes of searching resources

This article deals with a two‐person zero‐sum game called a search allocation game (SAG), in which a searcher and a target participate as players. The searcher distributes his searching resources in a search space to detect the target. The effect of resources lasts a certain period of time and extends to some areas at a distance from the resources' dropped points. On the other hand, the target moves around in the search space to evade the searcher. In the history of search games, there has been little research covering the durability and reachability of searching resources. This article proposes two linear programming formulations to solve the SAG with durable and reachable resources, and at the same time provide an optimal strategy of distributing searching resources for the searcher and an optimal moving strategy for the target. Using examples, we will analyze the influences of two attributes of resources on optimal strategies. © 2007 Wiley Periodicals, Inc. Naval Research Logistics 2008     

Algorithms for the multi‐item multi‐vehicles dynamic lot sizing problem

We consider a two‐stage supply chain, in which multi‐items are shipped from a manufacturing facility or a central warehouse to a downstream retailer that faces deterministic external demand for each of the items over a finite planning horizon. The items are shipped through identical capacitated vehicles, each incurring a fixed cost per trip. In addition, there exist item‐dependent variable shipping costs and inventory holding costs at the retailer for items stored at the end of the period; these costs are constant over time. The sum of all costs must be minimized while satisfying the external demand without backlogging. In this paper we develop a search algorithm to solve the problem optimally. Our search algorithm, although exponential in the worst case, is very efficient empirically due to new properties of the optimal solution that we found, which allow us to restrict the number of solutions examined. Second, we perform a computational study that compares the empirical running time of our search methods to other available exact solution methods to the problem. Finally, we characterize the conditions under which each of the solution methods is likely to be faster than the others and suggest efficient heuristic solutions that we recommend using when the problem is large in all dimensions. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

A cooperative game in search theory

Search theory originates from the military research efforts of WWII. Most researchers of that period modeled their search games in noncooperative games, where players are enemies or compete against each other. In this article, we deal with a cooperative search game, where multiple searchers behave cooperatively. First we describe several search problems and discuss the possibility of a coalition or cooperation among searchers. For the cooperative search game, we define a function named quasi‐characteristic function, which gives us a criterion similar to the so‐called characteristic function in the general coalition game with transferable utility. The search operation includes a kind of randomness with respect to whether the searchers can detect a target and get the value of the target. We also propose a methodology to divide the obtained target value among members of the coalition taking account of the randomness. As a concrete problem of the cooperative search game, we take the so‐called search allocation game, where searchers distribute their searching resources to detect a target in a cooperative way and the target moves in a search space to evade the searchers. Lastly, we discuss the core of the cooperative search allocation game. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

搜索路径给定时的搜索对策问题及其应用

搜索路径给定时的最优搜索方案问题,也可以理解为是关于搜索者和目标的二人对策问题,主要讨论了当搜索路径给定时的单个搜索者和单个目标的搜索对策问题。首先根据问题的特点,利用动态规划和迭代的方法,确定关于目标逃逸路径混合策略的最优分区,证明该分区是多面体凸集;针对目标不同逃逸路径的分区,求出搜索者的最大期望收益,再将问题转化为二人有限零和对策,计算出搜索者的支付矩阵,确定最优搜索策略。最后结合海军护航行动,对我舰载直升机搜索小型海盗船进行分析和计算,说明搜索路径给定时的最优搜索对策对于双方的资源分配和提高搜索效率具有一定的应用价值。     

一类对固定目标的集群搜寻对策问题及求解

利用集群搜索对策的理论与方法 ,建立了集群对固定目标的一类搜索对策模型 ,给出了集群的ε -最优搜寻策略 ,并考虑了其在搜索过程中的应用     

Rendezvous search when marks are left at the starting points

Leaving marks at the starting points in a rendezvous search problem may provide the players with important information. Many of the standard rendezvous search problems are investigated under this new framework which we call markstart rendezvous search. Somewhat surprisingly, the relative difficulties of analysing problems in the two scenarios differ from problem to problem. Symmetric rendezvous on the line seems to be more tractable in the new setting whereas asymmetric rendezvous on the line when the initial distance is chosen by means of a convex distribution appears easier to analyse in the original setting. Results are also obtained for markstart rendezvous on complete graphs and on the line when the players' initial distance is given by an unknown probability distribution. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 722–731, 2001     

智能搜救机器人在障碍地形的自主构型规划

为了解决带有辅助摆臂的智能搜救机器人自动规划构型以实现自主越障的难题,提出一种能够适应复杂地面形状的搜救机器人越障构型规划新方法,其核心是一种高适应性、高效率的机器人姿态预测算法。通过将地形表示为离散的点集,建立了搜救机器人的单侧姿态预测数学模型;进一步提出了快速求解该问题的算法,每秒可预测1 000～1 500个姿态。基于此,设计了机器人越障过程中状态、动作的评价指标,运用动态规划算法与滚动优化思想构建了具有优化能力的、能够实时运行的构型规划器。仿真与实物实验的结果表明,该方法能够使机器人自主调整构型穿越复杂地形,且相较强化学习算法和人工操作具有更平稳的越障效果。     

Heuristics for the location of inspection stations on a network

This article considers the preventive flow interception problem (FIP) on a network. Given a directed network with known origin‐destination path flows, each generating a certain amount of risk, the preventive FIP consists of optimally locating m facilities on the network in order to maximize the total risk reduction. A greedy search heuristic as well as several variants of an ascent search heuristic and of a tabu search heuristic are presented for the FIP. Computational results indicate that the best versions of the latter heuristics consistently produce optimal or near optimal solutions on test problems. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 287–303, 2000