进化规划中的变异与收敛

进化规划算法中变异是唯一的操作,因此变异算子对进化规划算法的性能有决定性的影响。文中以高斯变异算子为例,研究了变异算子在进化进程的作用,分析了进化规划算法不收敛的原因以及变异算子与进化代数、收敛精度间的关系。对传统进化规划算法和多群进化规划算法的性能进行了仿真研究,仿真结果表明了分析结果的正确性。     

区域防空导弹反导火力分配研究

分析了传统防空导弹火力分配模型的不足,考虑到编队内各舰艇近程防空作战能力的不同,结合装备性能特点,建立了基于机会约束规划的区域防空导弹火力分配优化模型。给出了基于遗传算法和BP神经网络的混合智能算法,该算法在精度和速度上均能满足防空作战的要求。     

Subspace dynamic‐simplex linear interpolation search for mixed‐integer black‐box optimization problems

Design and management of complex systems with both integer and continuous decision variables can be guided using mixed‐integer optimization models and analysis. We propose a new mixed‐integer black‐box optimization (MIBO) method, subspace dynamic‐simplex linear interpolation search (SD‐SLIS), for decision making problems in which system performance can only be evaluated with a computer black‐box model. Through a sequence of gradient‐type local searches in subspaces of solution space, SD‐SLIS is particularly efficient for such MIBO problems with scaling issues. We discuss the convergence conditions and properties of SD‐SLIS algorithms for a class of MIBO problems. Under mild conditions, SD‐SLIS is proved to converge to a stationary solution asymptotically. We apply SD‐SLIS to six example problems including two MIBO problems associated with petroleum field development projects. The algorithm performance of SD‐SLIS is compared with that of a state‐of‐the‐art direct‐search method, NOMAD, and that of a full space simplex interpolation search, Full‐SLIS. The numerical results suggest that SD‐SLIS solves the example problems efficiently and outperforms the compared methods for most of the example cases. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 305–322, 2017     

类“标枪”导弹两栖登陆反装甲作战弹道仿真分析

两栖登陆作战在战术上是最复杂、最危险的作战行动,登陆部队需要面对抗登陆方坚固的海岸防御背水抢滩作战,其危险性和困难可想而知。"工欲善其事,必先利其器",在兵器上的优势成为克服不利地理条件,形成火力优势的关键。类"标枪"反装甲导弹装备是两栖登陆作战中单兵反装甲作战的主要武器,仿真技术是类"标枪"反装甲导弹武器系统优化设计和性能研究的必要手段。介绍了单项仿真与综合仿真相结合的仿真方法,给出了类"标枪"反装甲导弹的弹道模型,利用Matlab编程语言进行了仿真验证,对改善导弹的弹道性能具有明显的实用价值。     

分布式海战场资源规划问题

分布式海战场资源规划是实现海上联合作战的关键。首先分析了海战场资源的分类及战场资源规划特点,建立了基于多智能体的分布式海战场资源规划系统,深入分析了该规划系统的组成和功能,并构造了相应的资源规划结构模型,为实现定性和定量相结合的海战场资源规划与管理提供了一条有效的途径。     

基于运动合成的小推力轨道优化方法

针对小推力轨道优化设计问题,提出一种基于运动合成的新方法。给出基于运动合成的小推力轨道机动表达方式,将小推力轨道运动分解成相对独立的三项:单独考虑日心引力的二体轨道运动,单独考虑小推力的运动,以及小推力的存在引起的日心引力摄动作用下的运动。分别给出各项运动的解析表达式,通过合成叠加得到小推力轨道的近似解析解。在此基础上,将小推力轨道优化问题转化成非线性规划问题,并利用序列二次规划方法求解。以小行星1989ML、火星和金星交会任务为例分别进行仿真实验,结果表明,所设计轨道满足任务约束,验证了该方法具有可用性和高效性。     

基于SDP松弛的干扰资源优化分配技术研究

提出一种基于semidefinite programming(简称SDP)松弛的干扰资源优化分配算法。在问题优化过程中首先对模型中非凸的约束条件进行松弛,变为凸约束,将原来的数学模型转化成SDP求解形式,利用内点算法对松弛后的模型求解。该算法利用解析的手段使得干扰资源优化分配问题中的NP难问题在多项式时间内得以解决,并且有较高的可靠性。仿真结果验证了算法的有效性。     

Minimum violations and predictive meta‐rankings for college football

This article presents two meta‐ranking models that minimize or nearly minimize violations of past game results while predicting future game winners as well as or better than leading current systems—a combination never before offered for college football. Key to both is the development and integration of a highly predictive ensemble probability model generated from the analysis of 36 existing college football ranking systems. This ensemble model is used to determine a target ranking that is used in two versions of a hierarchical multiobjective mixed binary integer linear program (MOMBILP). When compared to 75 other systems out‐of‐sample, one MOMBILP was the leading predictive system while getting within 0.64% of the retrodictive optimum; the other MOMBILP minimized violations while achieving a prediction total that was 2.55% lower than the best mark. For bowls, prediction sums were not statistically significantly different from the leading value, while achieving optimum or near‐optimum violation counts. This performance points to these models as potential means of reconciling the contrasting perspectives of predictiveness versus the matching of past performance when it comes to ranking fairness in college football. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 61: 17–33, 2014     

Index policies for the routing of background jobs

Arriving (generic) jobs may be processed at one of several service stations, but only when no other (dedicated) jobs are waiting there. We consider the problem of how to route these incoming background jobs to make best use of the spare service capacity available at the stations. We develop an approximative approach to Whittle's proposal for restless bandits to obtain an index policy for routing. The indices concerned are increasing and nonlinear in the station workload. A numerical study testifies to the strong performance of the index policies developed. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Higher‐order Markov chain models for categorical data sequences*

In this paper we study higher‐order Markov chain models for analyzing categorical data sequences. We propose an efficient estimation method for the model parameters. Data sequences such as DNA and sales demand are used to illustrate the predicting power of our proposed models. In particular, we apply the developed higher‐order Markov chain model to the server logs data. The objective here is to model the users' behavior in accessing information and to predict their behavior in the future. Our tests are based on a realistic web log and our model shows an improvement in prediction. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004