遗传算法在目标跟踪中的传感器分配算法

传感器在进行目标跟踪时,常规算法主要通过线性规划建立传感器与目标之间的分配方法.但是在对多目标和多传感器的战场环境中,这些方法有一定局限性.研究了基于遗传算法的传感器分配方法,通过构造符合传感器分配这一特殊问题的染色体,从而形成初始种群,然后利用遗传算法模拟生物遗传迭代和自然选择的遗传机理,通过多次选择最终收敛于问题的一个满意解.仿真显示,在大数据运算的环境中,该算法有更高的可行性和有效性.     

Parallel machine scheduling with job assignment restrictions

In the classical multiprocessor scheduling problem independent jobs must be assigned to parallel, identical machines with the objective of minimizing the makespan. This article explores the effect of assignment restrictions on the jobs for multiprocessor scheduling problems. This means that each job can only be processed on a specific subset of the machines. Particular attention is given to the case of processing times restricted to one of two values, 1 and λ, differing by at most 2. A matching based polynomial time ε‐approximation algorithm is developed that has a performance ratio tending to . This algorithm is shown to have the best possible performance, tending to 3/2, for processing times 1 and 2. For the special case of nested processing sets, i.e., when the sets of machines upon which individual jobs may be assigned are non‐overlapping, the behavior of list scheduling algorithms is explored. Finally, for assignment restrictions determined by just one characteristic of the machines, such as disc storage or memory constraint in the case of high performance computing, we contribute an algorithm that provides a 3/2 worst case bound and runs in time linear in the number of jobs. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

基于热经济学的舰船发电机组配置优化

针对舰船综合电力推进的特点,运用热经济学理论,建立了发电机组配置的数学优化模型.通过Matlab遗传算法工具箱,利用改进的遗传算法对发电机组的配置优化进行研究.结果表明,热经济学方法能较全面地反映舰船动力装置配置的经济性;改进的遗传算法是一种解决发电机组配置优化的有效方法.     

汽车辅助车闸的自适应控制

采用Guauss Seidel模型参数调整法 ,建立了辅助车闸位置控制装置的动态数学模型。在此基础上 ,运用超稳定理论设计了模型参考自适应位置控制系统 ,并在基于MATLAB软件包的硬件在环系统仿真平台上 ,进行系统的软、硬件混合仿真研究。试验表明理论仿真结果和系统实时响应吻合。从而 ,为在复杂环境下控制车速、车距提供了有效的实验技术手段和简捷的系统控制方法     

Mean sojourn times in multiclass feedback queues with gated disciplines

In this paper, we investigate multiclass feedback queues with gated disciplines. The server selects the stations by a nonpreemptive priority scheduling algorithm and serves customers in the selected station by either a gated FCFS discipline or a gated priority discipline. We take a rather systematic approach to their mean sojourn times. We define conditional expected sojourn times for all customers and derive their expressions from an analysis of busy periods. Since they are shown to be linear in some components of the system states, their steady state mean values can be derived from simple limiting procedures. These mean values can be obtained from a set of linear equations. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 719–741, 2003.     

The effectiveness of the longest delivery time rule for the flow shop delivery time problem

In the flow shop delivery time problem, a set of jobs has to be processed on m machines. Every machine has to process each one of the jobs, and every job has the same routing through the machines. The objective is to determine a sequence of the jobs on the machines so as to minimize maximum delivery completion time over all the jobs, where the delivery completion time of a job is the sum of its completion time, and the delivery time associated with that job. In this paper, we prove the asymptotic optimality of the Longest Delivery Time algorithm for the static version of this problem, and the Longest Delivery Time among Available Jobs (LDTA) algorithm for the dynamic version of this problem. In addition, we present the result of computational testing of the effectiveness of these algorithms. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

遗传算法在非线性回归模型辨识中的应用

对遗传算法在非线性回归模型辨识中的应用进行了探讨,切削温度回归模型辨识的实例表明,该方法是有效的.     

复杂电磁环境下的电磁频谱管理效能评估研究

针对复杂电磁环境下的电磁频谱管理效能评估问题,提出一套系统地效能评估方法.首先对效能评估的指标体系进行了分析,然后提出了一种多模型混合的效能评估方法,最后对整个过程中效能评估的流程进行研究.通过实例仿真研究表明,该方法可以有效地对复杂电磁频谱下的电磁频谱管理效能进行评估.     

基于遗传算法的虚拟物流联合库存控制研究

针对随机需求条件下的虚拟物流库存控制问题进行了深入研究，提出了一种新的联合库存控制策略——（T，S，s）策略，建立了相应的库存成本模型，并构造遗传算法对模型进行求解。结果分析表明，所提出的（T，S，S）联合库存控制策略是有效的。     

混合模糊测试中混合符号执行优化策略评估与分析

针对传统混合模糊测试提升技术多聚焦于利用多种动静态分析手段辅助而忽略了混合符号执行自身性能的问题,提出一种混合模糊测试平衡点模型,并基于该模型对主流混合符号执行方案进行剖析,包括污点分析辅助模糊测试、混合模糊测试以及混合符号执行,归纳了6种符号执行方案,基于混合符号执行引擎Triton复现了6种符号执行方案,并通过10个典型真实程序进行了测试评估。从效率、内存、覆盖率三个维度对各个方案进行性能对比与影响因素分析。实验证明,优化方案都可以消除不必要的约束并减少时间和空间开销,但约束缩减会造成信息丢失,造成覆盖率降低。基于实验数据分析,提出了一个优化方案的性能序列,并提出三种针对不同测试需求的优化方案。