基于随机漫游模型的协同搜索力最优分配方法

针对多平台协同搜索的最优搜索问题,以多无人机区域搜索任务为背景,将搜索论和随机规划引入到编队协同搜索中,建立了环境模型、无人机模型、传感器模型;为了解决目标丢失后的“应召”搜索问题,建立了目标的随机漫游模型;通过对搜索力最优分配问题的分析,认为其实质为一类线性规划问题,提出了一种基于递归原理的解算方法;最后,通过仿真计算,证明了该随机漫游模型的合理性,并验证了所提算法的有效性。     

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。     

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。     

多平台协同搜索水雷效能分析

侦察水雷是水雷战的一项重要内容。在水下无人作战平台和航空反水雷直升机作战平台搜索水雷概率模型分析基础上,给出了多平台协同搜索水雷方案优化模型,经分析归纳得到多平台协同搜索水雷最优方案,可为实际作战中多平台协同搜索水雷方案的制定、优化提供决策支持,具有较高的实用性。     

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。     

火力分配多目标优化的IBACO算法

应用蚁群优化算法(Ant Colony Optimization)求解多目标优化问题已经引起广泛关注,多目标火力分配问题的目标是求出一个合适的武器目标分配方案,使满足决策需要。建立了多目标火力分配的数学模型,提出一种基于指标的蚁群优化算法Indicator-Based Ant Colony Optimization),给出了算法的具体步骤。IBACO的核心思想是利用二元性能指标来引导人工蚂蚁进行搜索,由于该算法中的信息素是根据指标的值来更新的,通过奖励信息素可以强化最优解。仿真实验证明了该算法的有效性,在解决火力分配问题上,所提算法和蚁群优化算法相比具有较好的收敛性。     

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。     

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。     

序降应力加速寿命试验(下)——优化设计篇

如何设计试验方案使试验评估结果更准确、试验代价更小,是序降应力加速寿命试验应用中面临的一个重要问题。以试验评估精度和试验代价共同需求为背景,建立一类新的基于加权系数的优化目标函数。为解决仿真优化设计过程中的计算量问题,在深入分析目标函数性质基础上,提出一种新的优化设计法——正交搜索法。与优化设计过程的全局搜索法不同,该方法能够逐次缩小目标函数值,快速逼近最优试验方案。最后通过仿真算例验证了新方法的正确性和高效性。     

优化多星协同观测的改进广义模式搜索算法

多星协同观测可以最大化卫星的整体效能,如何对多星进行部署是一个设计空间大、设计变量多的优化问题.对此,提出了基于Kriging模型的改进广义模式搜索算法.在算法的搜索步,通过代理模型最优和最大期望提高在当前网格内进行选点,避免选择的盲目性;在筛选步,利用代理模型预测筛选集中各点提高的比例并排序,减少不必要的仿真分析.最后,采用该算法对多星部署方案进行优化,通过对比发现,算法性能优于STK-Analyzer,证明了算法的可行性和有效性.     

Integrated production scheduling and preventive maintenance planning for a single machine under a cumulative damage failure process

This paper finds the optimal integrated production schedule and preventive maintenance plan for a single machine exposed under a cumulative damage process, and investigates how the optimal preventive maintenance plan interacts with the optimal production schedule. The goal is to minimize the total tardiness. The optimal policy possesses the following properties: Under arbitrary maintenance plan when jobs have common processing time, and different due dates, the optimal production schedule is to order the jobs by earliest due date first rule; and when jobs have common due date and different processing times, the optimal production schedule is shortest processing time first. The optimal maintenance plan is of control limit type under any arbitrary production schedule when machine is exposed under a cumulative damage failure process. Numerical studies on the optimal maintenance control limit of the maintenance plan indicate that as the number of jobs to be scheduled increases, the effect of jobs due dates on the optimal maintenance control limit diminishes. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

基于变量节点串行消息传递的LDPC码译码研究

针对标准LDPC码译码中洪水消息传递机制的不足,提出以串行机制进行消息传递,按照变量节点的顺序进行消息处理和传递,对每个变量节点同时接收校验消息和发送变量消息。该方法使更新的消息能够很快进入当前迭代计算,改善了LDPC迭代译码的收敛性能。通过对几种常用译码算法的仿真比较,验证了在复杂度不增加的情况下,该方法性能优于其它几种最大后验概率准则的译码方法,且算法收敛快,是一种能较好兼顾性能与实现复杂度的译码方法。     

Optimal lot sizing and inspection policy for an EMQ model with imperfect inspections

An EMQ model with a production process subject to random deterioration is considered. The process can be monitored through inspections, and both the lot size and the inspection schedule are subject to control. The “in-control” periods are assumed to be generally distributed and the inspections are imperfect, i.e., the true state of the process is not necessarily revealed through an inspection. The objective is the joint determination of the lot size and the inspection schedule, minimizing the long-run expected average cost per unit time. Both discrete and continuous cases are examined. A dynamic programming formulation is considered in the case where the inspections can be performed only at discrete times, which is typical for the parts industry. In the continuous case, an optimum inspection schedule is obtained for a given production time and given number of inspections by solving a nonlinear programming problem. A two-dimensional search procedure can be used to find the optimal policy. In the exponential case, the structure of the optimal inspection policy is established using Lagrange's method, and it is shown that the optimal inspection times can be found by solving a nonlinear equation. Numerical studies indicate that the optimal policy performs much better than the optimal policy with periodic inspections considered previously in the literature. The case of perfect inspections is discussed, and an extension of the results obtained previously in the literature is presented. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 165–186, 1998     

Deterministic inventory lot‐size models under inflation with shortages and deterioration for fluctuating demand

In this paper, we extend the inventory lot‐size models to allow for inflation and fluctuating demand (which is more general than constant, increasing, decreasing, and log‐concave demand patterns). We prove that the optimal replenishment schedule not only exists but is also unique. Furthermore, we show that the total cost associated with the inventory system is a convex function of the number of replenishments. Hence, the search for the optimal number of replenishments is simplified to finding a local minimum. Finally, several numerical examples are provided to illustrate the results. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 144–158, 2001     

Scheduling patients in an ambulatory surgical center

This paper presents a deterministic approach to schedule patients in an ambulatory surgical center (ASC) such that the number of postanesthesia care unit nurses at the center is minimized. We formulate the patient scheduling problem as new variants of the no‐wait, two‐stage process shop scheduling problem and present computational complexity results for the new scheduling models. Also, we develop a tabu search‐based heuristic algorithm to solve the patient scheduling problem. Our algorithm is shown to be very effective in finding near optimal schedules on a set of real data from a university hospital's ASC. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Total optimality of incrementally optimal allocations

This paper considers the problem of finding optimal solutions to a class of separable constrained extremal problems involving nonlinear functionals. The results are proved for rather general situations, but they may be easily stated for the case of search for a stationary object whose a priori location distribution is given by a density function on R, a subset of Euclidean n-space. The functional to be optimized in this case is the probability of detection and the constraint is on the amount of effort to be used Suppose that a search of the above type is conducted in such a manner as to produce the maximum increase in probability of detection for each increment of effort added to the search. Then under very weak assumptions, it is proven that this search will produce an optimal allocation of the total effort involved. Under some additional assumptions, it is shown that any amount of search effort may be allocated in an optimal fashion.     

Optimal production and maintenance policy for imperfect production systems

A joint optimization of the production run length and preventive maintenance (PM) policy is studied for a deteriorating production system where the in‐control period follows a general probability distribution with non‐decreasing failure rate. In the literature, the sufficient conditions for the optimality of the equal‐interval PM schedule is explored to derive an optimal production run length and an optimal number of PM actions. Nevertheless, an exhaustive search may arise. In this study, based on the assumption that the conditions for the optimality of the equal‐interval PM schedule hold, we derive some structural properties for the optimal production/PM policy, which increases the efficiency of the solution procedure. These analyses have implications for the practical application of the production/PM model to be more available in practice. A numerical example of gamma shift distribution with non‐decreasing failure rates is used to illustrate the solution procedure, leading to some insight into the management process. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

A two product dynamic economic lot size production model with either-or production constraints

This paper considers the production of two products with known demands over a finite set of periods. The production and inventory carrying costs for each product are assumed to be concave. We seek the minimum cost production schedule meeting all demands, without backlogging, assuming that at most one of the two products can be produced in any period. The optimization problem is first stated as a nonlinear programming problem, which allows the proof of a result permitting the search for the optimal policy to be restricted to those which produce a product only when its inventory level is zero. A dynamic programming formulation is given and the model is then formulated as a shortest route problem in a specially constructed network.     

求解整数规划问题的一个搜索方法

本文整数规划问题给出一种搜索方法,它类似于求解连续变量优化问题的迭代方法,从一个好的初始可行解出发,寻找一个搜索方向,沿着这个方向求出改进的可行解,然后又开始下一次迭代。此方法简单易行,可以求出问题的最优解或近似最优解,对于整数线性规划问题和整数非线性规划问题的求解都适用,并且容易推广到求解大规校整数线性规划问题。文中附有计算例子,说明方法是有效的。     

Contract award analysis by mathematical programming

ABSTRACT A large manufacturer of telephone directories purchases about 100,000 tons of paper annually from several paper mills on the basis of competitive bids. The awards are subject to several constraints. The principal company constraint is that the paper must be purchased from at least three different suppliers. The principal external constraints are: 1) one large paper mill requires that if contracted to sell the company more than 50,000 tons of paper, it must be enabled to schedule production over the entire year; 2) the price of some bidders is based on the condition that their award must exceed a stipulated figure. The paper shows that an optimal purchasing program corresponds to the solution of a model which, but for a few constraints, is a linear programming formulation with special structure. The complete model is solved by first transforming it into an almost transportation type problem and then applying several well-known L.P. techniques.