基于聚类算法的多无人机系统任务分配

针对现有任务分配方法在任务点较多时不易解算,且计算量大的问题,提出了基于模糊C-均值聚类算法的多无人机系统任务分配方法.首先,利用模糊C-均值聚类算法得到的隶属度矩阵对任务点进行初始分配;其次,针对基于空间划分聚类可能造成各UAV任务不均衡的问题,设计任务的局部优化调整规则;最后,结合单旅行商问题,利用Tabu Sea...     

舰船航向保持的变结构控制及仿真

运用变结构控制理论和计算机仿真技术研究舰船航向保持过程的变结构控制问题,针对舰船定向航行要求航向准、舵角小的控制特点,采用二次型最优控制方法设计滑动模态超平面,设计了满足滑模超平面到达条件的指数趋近律,导出了对应的控制律。同时,为进行比较研究,设计了PID控制器并整定了相关参数。理论分析与仿真研究表明:对于舰船定向航行,变结构控制方案正确可行,控制效果优于PID控制方案。     

防空系统目标威胁评估与火力分配模型

首先运用层次分析法建立了防空系统对空袭目标价值评估模型的层次结构,并获得空袭目标的价值权重系数。其次,在综合考虑目标价值权重的基础上,运用模糊决策的方法推导出防空系统目标威胁综合评估数学模型。最后运用军事运筹学0-1整数规划的方法,给出了防空系统目标优化火力分配0-1整数规划数学模型。     

A stochastic model for burn‐in procedures in accelerated environment

Burn‐in procedure is a manufacturing technique that is intended to eliminate early failures of system or product. Burning‐in a component or system means to subject it to a period of use prior to being used in field. Generally, burn‐in is considered expensive and so the length of burn‐in is typically limited. Thus, burn‐in is most often accomplished in an accelerated environment in order to shorten the burn‐in process. A new failure rate model for an accelerated burn‐in procedure, which incorporates the accelerated ageing process induced by the accelerated environmental stress, is proposed. Under a more general assumption on the shape of failure rate function of products, which includes the traditional bathtub‐shaped failure rate function as a special case, upper bounds for optimal burn‐in time will be derived. A numerical example will also be given for illustration. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

改进遗传算法求解电力网攻击无人机分队任务分配

遗传算法因其出色的寻优能力,自提出后就被广泛用于工程技术上的最优化问题求解。根据电力网攻击无人机分队任务分配的实际需要,提出基于遗传算法思想的解决方案,并在原算法基础上,采用种群分组进化的策略进行改进。详细介绍算法的基本原理和仿真步骤,再举出实际算例进行仿真,实验结果证明算法的改进取得了良好效果。     

电传动装甲车辆电源系统建模与仿真

电源系统是电传动装甲车辆的核心,对其进行建模与仿真研究具有重要意义。电源系统的非线性特性导致了建模困难、模型精度低以及模型实用性差等难题,针对不同的部件特性采取不同的方法建立其仿真模型,完成了基于模糊控制的系统多目标优化功率分配策略研究。并在此基础上进行了部件和系统两个层次的仿真试验,证明所建模型能够较好地反映电传动车辆电源系统的工作特性。     

A learning tabu search for a truck allocation problem with linear and nonlinear cost components

The two‐level problem studied in this article consists of optimizing the refueling costs of a fleet of locomotives over a railway network. The goal consists of determining: (1) the number of refueling trucks contracted for each yard (truck assignment problem denoted TAP) and (2) the refueling plan of each locomotive (fuel distribution problem denoted FDP). As the FDP can be solved efficiently with existing methods, the focus is put on the TAP only. In a first version of the problem (denoted (P1)), various linear costs (e.g., fuel, fixed cost associated with each refueling, weekly operating costs of trucks) have to be minimized while satisfying a set of constraints (e.g., limited capacities of the locomotives and the trucks). In contrast with the existing literature on this problem, two types of nonlinear cost components will also be considered, based on the following ideas: (1) if several trucks from the same fuel supplier are contracted for the same yard, the supplier is likely to propose discounted prices for that yard (Problem (P2)); (2) if a train stops too often on its route, a penalty is incurred, which represents the dissatisfaction of the clients (Problem (P3)). Even if exact methods based on a mixed integer linear program formulation are available for (P1), they are not appropriate anymore to tackle (P2) and (P3). Various methods are proposed for the TAP: a descent local search, a tabu search, and a learning tabu search (LTS). The latter is a new type of local search algorithm. It involves a learning process relying on a trail system, and it can be applied to any combinatorial optimization problem. Results are reported and discussed for a large set of instances (for (P1), (P2), and (P3)), and show the good performance of LTS. © 2014 Wiley Periodicals, Inc. 62:32–45, 2015     

Optimal service‐capacity allocation in a loss system

We consider a loss system with a fixed budget for servers. The system owner's problem is choosing the price, and selecting the number and quality of the servers, in order to maximize profits, subject to a budget constraint. We solve the problem with identical and different service rates as well as with preemptive and nonpreemptive policies. In addition, when the policy is preemptive, we prove the following conservation law: the distribution of the total service time for a customer entering the slowest server is hyperexponential with expectation equal to the average service rate independent of the allocation of the capacity. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 81–97, 2015     

适用于认知无线传感器网络的高效频谱分配方法

广泛工作在ISM(Industrial,Scientific and Medical)频段的无线传感器网络面临严重的频谱稀缺问题。在无线通信中,动态频谱分配被认为是提高频谱效能的重要途径。针对典型集中式管理的认知无线传感器网络设计了基于图着色结合负载强度的高效频谱分配算法。首先在协议干扰模型下确保频谱资源在空间上充分利用,随后综合考虑节点负载强度与公平性建立优化模型并按照乘子法加拟牛顿法框架求解最优值。仿真实验表明算法与固定频谱分配方式和传统自适应频谱分配算法相比,在系统吞吐量和节点缓冲区队列长度两个关键性能指标上具有显著优势。     

Budget allocation,national security,military intelligence,and human capital: a dynamic model

This study develops a dynamic model that integrates military intelligence into the defense capability of the country and the optimal allocation of its government budget. We assert that the effectiveness of the country’s military intelligence is contingent on the quality of its human capital, which, in turn, implies a long-term positive relationship between the government’s various civilian expenditures and its capacity to achieve a cost-effective intelligence and, hence, military capability. This relationship is developed within a multiple-period arms race model between two rivals. Using this model and stylized data for the Israeli–Syrian arms race, we show that an appropriate budget shift from defense to civilian expenditures during the initial periods of the planning horizon will gradually (over a decade, say) increase the quality of human capital in the country and, thus, the effectiveness of its intelligence, which, in turn, will increase the country’s future security and welfare.