基于遗传算法对规避目标搜索模型

分析了在应召条件下对规避目标搜索行动的特点,然后采用遗传算法建立了可用于辅助搜索决策制定协同搜索方案的模型,为分析应召搜索提供了新的方法,该方法克服了传统的运筹学搜索论在协同行动等复杂条件下寻求最优搜索方案的不足。     

直升机应召搜潜中一种快速搜索方式研究

本文根据直升机应召搜潜的基本原理,描述了直升机搜潜设备搜索潜艇目标的运动状态,建立了直升机搜潜设备探测装置与潜艇相对运动的搜索模型,给出了直升机最优搜索运动航线,解决了直升机应召搜潜时如何快速搜潜的难题。     

“应召”搜索问题的最优搜索路线

解决了确定性二次搜索（即“应召”搜索）问题的最优搜索路线。在搜索时间期望值最小、最远可能航程最短、最长可能时间最短三个准则下分别找出了相应的最优搜索路线,并从理论上严格证明了三者的统一性。这个结论在军事领域具有很重要的应用价值     

基于混合算法的实时订货信息下的车辆调度优化

实时订货信息下的车辆调度是随机性车辆调度中货物需求量、需求点均不确定的情况下的车辆调度.针对该问题,本文构建了配送总成本最小的目标函数,提出了采用混合算法求解的思路.即以局部搜索法求得初始解,采用遗传算法优化初始解,并在送货时间更新后,利用禁忌搜索法求解速度快的特点改进调度方案,得到订货信息不断更新的条件下的车辆调度方案.通过实例分析,本方法既可解决电子商务条件下实时订货的车辆调度问题,也具有求解结果可靠、求解过程快速的特点.     

Goldstein线搜索下Levenberg-Marquardt方法的全局收敛性

给出在Goldstein线搜索条件下求解非线性方程的Levenberg-Marquardt方法, 在较为温和的条件下证明了该方法的全局收敛性, 并且利用该方法对广义互补问题进行了求解分析.     

基于QoS协同关联的改进Skyline制造服务组合优化方法

服务社会网络环境下,云制造服务通过与其他参与同一任务的服务共享与竞争物理设备、信息、知识等资源形成协同效应,对双方实际执行效果具有重要影响,导致出现QoS偏离现象,现有服务选择模型难以适应这一情景。根据服务协同网络特点,本文提出基于QoS协同关联的制造服务组合方法。运用QoS协同关联和协同系数表达资源共享、冲突对QoS的影响程度,构建了新的服务选择优化模型。基于创新Skyline服务对概念,改善了Skyline算法在QoS协同关联条件下的搜索效率和结果,通过智能汽车制造仿真实验,验证了本文模型和算法的有效性。     

一种新的三项超记忆梯度方法

提出了一种三项超记忆梯度方法.该方法的最大优点是:在无需线性搜索的条件下,迭代方向就是充分下降方向.在较弱的条件下,分析了方法的全局收敛性.初步数值试验表明方法是有效的.     

应急不完全信息环境下的混合多属性协同决策方法

科学的应急救援协同决策理论方法,不但能使应急管理系统更好地发挥作用,而且能使政府及公众的应急救援行为更加规范和有序.为此,针对应急环境下决策信息不完全的背景,研究构建了一类综合集成网络层次分析法(ANP)、证据理论(D-SEvidence Theory)以及改进的理想点法(TOPSIS)的混合多属性应急协同决策方法.其中ANP用于处理应急救援方案非独立和相互联系的评价指标权重的确立,D-S Theory用于处理不完全信息条件下多个部门对应急救援候选方案的不同评价信息融合,改进的理想点法(TOPSIS)则用于最终候选应急救援方案的排序.研究结果表明,所提出的混合多属性协同决策方法不仅在理论上有所集成创新,而且在实际应用中可以有效解决应急环境下多部门或多环节协同决策问题.     

一类基于Wolfe线搜索下的谱共轭梯度法

在已有文献β■的基础上得到了一个新的谱共轭参数,从而构造了一个新的谱共轭梯度法.并且新方法的搜索方向不需要任何线性搜索条件而自动下降.利用标准Wolfe线搜索,在一般假设条件下,验证了该方法是全局收敛的.     

一类满足充分下降条件和自适应共轭性的修正THREECG方法北大核心CSCD

基于CG_DESCENT方法和自适应的共轭条件,本文提出了一类修正的THREECG共轭梯度法.该方法在每步迭代中都不依赖于函数的凸性和搜索条件而自行产生充分下降方向.在适当的条件下,获证了在Wolfe搜索下算法求解一般函数时具有全局收敛性.同时,数值实验表明本文算法可以有效求解测试问题.     

A two-cell model of search for an evading target

A form of game-theoretic model is proposed for the problem of search for an evading target. The region of search is divided into two cells, with the evader starting in the first cell and having the objective of moving from there, through the second to some goal area, without being detected. Optimal searcher strategy is derived in analytical form for some special cases of practical interest. The results indicate that if there is any difference in detectability in the two cells, then there is optimally a rather large concentration of search effort in the more favourable cell. The special cases are also compared numerically with some more general situations. Although both the model and the solution are relatively simple, they serve to demonstrate the potential value of this form of approach to the problem, as well as the complexity of the problem for more general situations.     

Object search. Dynamics. Geometry. Graphics

The paper describes certain geometric methods for solution of the search problem of several searching and several evading objects in the plane. __________ Translated from Fundamental’naya i Prikladnaya Matematika (Fundamental and Applied Mathematics), Vol. 11, No. 1, Geometry, 2005.     

追捕与逃跑策略

<正>首先讨论的是单个捕食者的几种捕食策略及相应的被捕食者的几种逃跑策略.捕食策略包括直追(SF).全预测(FF)和不完全预测(PF)策略.相应的逃跑策略有直线逃跑(sLE).先直线跑后转弯(FSTD)和反预测策略. 我们按照捕食策略和逃跑策略的一物降一物原则来发展这些策略,分别如下: 逃跑策略SLE FSTD AF; 追捕策略SF FF PF. 通过比较,我们认为对于THes采用AF策略最有利,而且Velo采用PF策略最有利. 对于上述策略,用我们对某些参数的估计值代入计算,得到Thes初始转弯距离的最佳值为1.6m,相应的Thes存活概率为0.656.     

Evasion of a fixed sphere by a dynamical object driven by a bounded force

A solution is obtained of the problem of synthesizing the control of the motion of a dynamical object (a point mass) evading a fixed spherical obstacle under the action of a bounded force. The set of all points for which evasion is possible is constructed in phase space (of arbitrary dimension), and control modes are constructed for bounded (fixed) and unbounded time intervals. The characteristics of the optimal motion, in particular, the time and minimum distance, are determined for specific initial data. The qualitative properties of the controlled motion are established.     

Optimal searching for a Helix target motion

This paper discusses a search problem for a Helix target motion in which any information of the target position is not available to the searchers. There exist three searchers start searching for the target from the origin. The purpose of this paper is to formulate a search model and finds the conditions under which the expected value of the first meeting time between one of the searchers and the target is finite. Also, the existence of the optimal search plan that minimizes the expected value of the first meeting time is shown. Furthermore,this optimal search plan is found. The effectiveness of this method is illustrated by using an example with numerical results.     

Optimal ambushing search for a moving target

This paper investigates a search problem for a moving target in which a searcher can anticipate the probabilities of routes selected by the target but does not have any time information about when the target transits the route. If the searcher had some time information, he could develop an efficient search plan by varying allocations of search effort based on time. Due to the lack of time information, the searcher must ambush the target by distributing search effort to places where the target is likely to pass. There are few papers that deal mathematically with this type of search problem with no time information. Employing the criterion of detection probability, we formulate the problem and obtain necessary and sufficient conditions for the optimal solution. By applying the conditions, we propose two methods for solving the problem. The convex programming problem can be easily solved numerically by some well-known methods, e.g. the gradient projection method or the multiplier method. By numerical comparison, it is verified that the proposed methods have the excellent performance in computational time. We also elucidate some properties of the optimal distribution of search effort by some numerical examples.     

Optimal discrete search with imperfect specificity

A target is hidden in one of several possible locations, and the objective is to find the target as fast as possible. One common measure of effectiveness for the search process is the expected time of the search. This type of search optimization problem has been addressed and solved in the literature for the case where the searcher has imperfect sensitivity (possible false negative results), but perfect specificity (no false positive detections). In this paper, which is motivated by recent military and homeland security search situations, we extend the results to the case where the search is subject to false positive detections.     

On the minimality of search paths under absolutely continuous univariate distributions

The linear search problem is concerned with the search for a target located randomly on a line. The target being sought for might be on either side of some starting point. A searcher makes for the target with an upper bound on his speed, using a continuous search path in which he changes his direction many times before reaching his goal. The minimality of average distance (time) from the starting point upon reaching the target is the measure of optimality of search paths. We have obtained sufficient conditions that guarantee the minimality of such search paths whenever the target has an absolutely continuous distribution.

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Zusammenfassung Ein Objekt, das sich in zufälliger Position auf einer Strecke befindet, soll gesucht werden; der Startpunkt liegt im Inneren der Strecke. Für die Bewegungsgeschwindigkeit bei der Suche ist eine obere Schranke gegeben; der Suchpfad muß stetig sein, wobei beliebig viele Richtungsänderungen zugelassen sind. Das Ziel ist die Minimierung der erwarteten Zeit bis zum Erreichen des Objekts. Unter der Voraussetzung einer absolut stetigen Verteilung für die Position des Objekts werden hinreichende Bedingungen für die Optimalität eines Suchpfades angegeben.

     

Multiplicative linear search for a brownian target motion

This paper investigates a search problem for a brownian target motion on one of n-intersected real lines in which any information of the target position is not available to the searchers all the time. We have n-searchers start searching for the target from the origin that is the intersection point of these lines. Each of the searchers moves continuously along his line in both directions of the starting point. The purpose of this paper is to formulate a search model and find the condition under which the expected value of the first meeting time between one of the searchers and the target is finite. Also, we show the existence of the optimal search plan which minimizes the expected value of the first meeting time and find it.     

A representation for the posterior distribution of the location of a moving target

A target moves according to a continuous stochastic process in Euclidean R_^H. A search is conducted by choosing a search strategy and by observing the state of a detection process. Methods for representing the posterior distributions for target location given no detection are discussed. In particular, methods for parameterizing Gaussian models for target motion and the transition intensity of the detection process which yield tractable representations are introduced. The methodology is discussed in terms of two examples.