文章编号：基于多目标进化搜索算法的AUV地磁仿生导航方法

针对水下自主航行器(AUV)地磁多参量多目标搜索的问题,提出了一种基于磁趋势敏感的多目标进化搜索算法。在进化算法的结构下,利用地磁场参量与导航路径的约束关系,以磁趋势敏感作为后验评估准则,建立导航模型,使得地磁多分量伴随航行器的运动同时同地收敛至各自目标值,实现导航目的。通过与六边形路径搜索算法的仿真对比,验证了多目标进化搜索算法的有效性和优越性。     

不确定条件下装备器材供应网规划模型

装备器材供应网是装备器材供应保障工作的重要基石,其规划问题是我军装备器材保障过程的重要战略决策之一。针对节点、边和需求的不确定性,对不确定条件下由多个区域供应子网构成的装备器材供应网的规划问题展开研究。针对问题的特点,用区间分析理论对供应网规划中的不确定性因素进行度量和运算,得到不确定性规划模型,通过区间运算转化,将不确定性模型转化为确定性混合整数规划模型,并设计采用基于禁忌搜索算法的两阶段算法进行求解,分别得到了不同参数设置下的模型求解结果,并将所用算法与模糊规划和随机规划算法的求解结果进行了比较分析。实例分析结果表明所建立的模型和算法具有较强的实用性。     

地磁仿生导航的多目标进化搜索算法

针对水下自主航行器地磁多参量多目标搜索的问题,提出一种基于磁趋势敏感的多目标进化搜索算法。在进化算法的结构下,利用地磁场参量与导航路径的约束关系,以磁趋势敏感作为后验评估准则,建立导航模型,使得地磁多分量伴随航行器的运动同时同地收敛至各自目标值,实现导航目的。通过与六边形路径搜索算法的仿真对比,验证了多目标进化搜索算法的有效性和优越性。     

Rendezvous of three agents on the line

This paper considers a three‐person rendezvous problem on the line which was introduced earlier by the authors. Three agents are placed at three consecutive integer value points on the real line, say 1, 2, and 3. Each agent is randomly faced towards the right or left. Agents are blind and have a maximum speed of 1. Their common aim is to gather at a common location as quickly as possible. The main result is the proof that a strategy given by V. Baston is the unique minimax strategy. Baston's strategy ensures a three way rendezvous in time at most 3.5 for any of the 3!2³ = 48 possible initial configurations corresponding to positions and directions of each agent. A connection is established between the above rendezvous problem and a search problem of L. Thomas in which two parents search separately to find their lost child and then meet again. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 244–255, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10005     

IRST 系统的数学仿真研究

讨论了目标红外辐射、大气传输和ＩＲＳＴ系统,并根据建立的数学模型,完成了ＩＲＳＴ系统的数学仿真研究。     

模糊随机过程的可分性与可测性

本文证明了一个模糊随机过程{_t(ω)t∈T}必存在一个与之等价的可分模糊随机过程{_t(ω)t∈T};且若模糊随机过程{_t(ω)t∈T}随机连续,则它存在等价的,可分且可测的模糊随机过程{■_t(ω)t∈T}。     

误差随机过程的一种数据预处理方法

在数据连续采集过程中,误差是一个随机的过程,有的误差数据出现“失真”,本文结合指挥仪综合检测中动态误差情况,提出一种平稳误差过程和非平稳误差过程的数据预处理方法。     

The (s,Q) inventory model with Erlang lead time and deterministic demand

We develop a simple, approximately optimal solution to a model with Erlang lead time and deterministic demand. The method is robust to misspecification of the lead time and has good accuracy. We compare our approximate solution to the optimal for the case where we have prior information on the lead‐time distribution, and another where we have no information, except for computer‐generated sample data. It turns out that our solution is as easy as the EOQ's, with an accuracy rate of 99.41% when prior information on the lead‐time distribution is available and 97.54–99.09% when only computer‐generated sample information is available. Apart from supplying the inventory practitioner with an easy heuristic, we gain insights into the efficacy of stochastic lead time models and how these could be used to find the cost and a near‐optimal policy for the general model, where both demand rate and lead time are stochastic. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

坦克分队遭遇战斗火力运用研究

根据遭遇战斗的特点,运用随机格斗、微分对策数理战术模型,研究坦克分队遭遇战斗最优火力运用策略问题.研究得出的结论符合坦克分队战术特点,为坦克分队指挥决策提供辅助作用.     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.