基于非独立测试的诊断策略优化生成

诊断策略优化设计是测试性设计中的一项重要内容.实际中的测试彼此间并非独立,即测试费用依赖于测试的先后顺序,针对这一问题,提出将测试划分成不同的测试模式,规定当一个测试序列中存在模式变换时必须考虑附加的转换费用.建立了同时考虑测试费用和模式转换费用启发式评估函数,并基于该启发式评估函数设计了近似最优的搜索算法,应用案例验证了本算法.试验表明该方法有效地解决了非独立测试的诊断策略优化生成问题.     

基于多QoS约束的启发式路由选择算法设计与实现

针对时延、路由跳数以及网络资源利率3种约束，结合软件路由器项目，对路由选择算法的网络模型进行了描述和定义，并提出了基于多QoS约束的启发式路由选择算法（H_MCP）。通过在软件路由器上实现和测试，表明该算法具有可行性和启发性。     

Decomposition-based approximation algorithms for the one-warehouse multi-retailer problem with concave batch order costs

We study the one-warehouse multi-retailer problem under deterministic dynamic demand and concave batch order costs, where order batches have an identical capacity and the order cost function for each facility is concave within the batch. Under appropriate assumptions on holding cost structure, we obtain lower bounds via a decomposition that splits the two-echelon problem into single-facility subproblems, then propose approximation algorithms by judiciously recombining the subproblem solutions. For piecewise linear concave batch order costs with a constant number of slopes we obtain a constant-factor approximation, while for general concave batch costs we propose an approximation within a logarithmic factor of optimality. We also extend some results to subadditive order and/or holding costs.     

Asymptotic analysis of periodic policies for the inventory routing problem

In this article, a distribution system is studied where the sum of transportation and inventory costs is to be minimized. The inventory holding cost is assumed to be the same for all retailers. A fixed partition (FP) periodic policy is proposed with tight asymptotic worst‐case performance of 3/2 with respect to the best possible policy. This bound cannot be improved in the class of FP periodic policies. In partition‐based PB policies, the retailers are first partitioned into sets and then the sets are grouped in such a way that sets of retailers within a group are served together at selected times. A PB periodic, policy is presented with tight worst‐case asymptotic performance of with respect to the best possible policy. This latter performance improves the worst‐case asymptotic performance of of the previously best known policy for this problem. We also show that the proposed PB periodic policy has the best worst‐case asymptotic performance within the class of PB policies. Finally, practical heuristics inspired by the analyzed policies are designed and tested. The asymptotic worst–case performances of the heuristics are shown to be the same of those of the analyzed policies. Computational results show that the heuristics suggested are less than 6.4% on average from a lower bound on the optimal cost when 50 or more retailers are involved. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 00: 000–000, 2013     

A generalized assignment model for dynamic supply chain capacity planning

We consider a generalization of the well‐known generalized assignment problem (GAP) over discrete time periods encompassed within a finite planning horizon. The resulting model, MultiGAP, addresses the assignment of tasks to agents within each time period, with the attendant single‐period assignment costs and agent‐capacity constraint requirements, in conjunction with transition costs arising between any two consecutive periods in which a task is reassigned to a different agent. As is the case for its single‐period antecedent, MultiGAP offers a robust tool for modeling a wide range of capacity planning problems occurring within supply chain management. We provide two formulations for MultiGAP and establish that the second (alternative) formulation provides a tighter bound. We define a Lagrangian relaxation‐based heuristic as well as a branch‐and‐bound algorithm for MultiGAP. Computational experience with the heuristic and branch‐and‐bound algorithm on over 2500 test problems is reported. The Lagrangian heuristic consistently generates high‐quality and in many cases near‐optimal solutions. The branch‐and‐bound algorithm is also seen to constitute an effective means for solving to optimality MultiGAP problems of reasonable size. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

面向动作序列的敏捷卫星任务规划问题

针对新一代敏捷卫星对地观测任务规划问题,考虑了直拍直传、立体成像、多条带拼接等复杂任务需求和观测、数据下传、对日定向等九种卫星动作,在任务规划的同时进行卫星动作规划。设计并实现了前瞻启发式构造算法,算法满足卫星存储、能量等复杂约束,在前瞻过程中每次决定当前任务是否安排。采用基于专家知识的多种启发式规则决定任务安排与安排卫星动作序列。仿真实例及实际工程应用表明,算法可以在很短的时间内给出较好的结果,证明了本文方法对于敏捷卫星任务规划问题的适用性。     

敏捷成像卫星自主规划模型与算法

针对敏捷成像卫星自主规划问题,将规划、决策、执行和信息反馈相结合,提出星上自主规划框架,并介绍框架结构和模块功能。在分析主要约束条件的基础上,建立基于时间线约束网络的问题模型。通过将各种卫星动作前后衔接,组合成能够完成不同任务的动作序列,提出一种面向卫星动作序列的启发式算法。该算法分为规划和决策两个部分,并在卫星执行每一个动作序列的同时基于多种启发式规则进行规划,在动作序列执行结束时进行决策。实验结果表明了自主规划框架和模型的合理性以及算法的有效性。     

电视侦察弹侦察效力的演化仿真优化研究

为了保证电视侦察弹能到达目标区域的上空并发挥最优的侦察效力,采用了基于遗传算法的启发式仿真优化方法来解决炮射电视侦察弹的优化使用问题.分析了电视侦察弹的主要影响因素,建立了用于计算目标侦察效力的仿真模型,引入了演化策略,实现了基于进化计算的启发式仿真优化系统,并求取了电视侦察弹的最大侦察效力及其主要影响因素的最优搭配....     

分布式火控系统实时通信的设计实现

实时可靠的通信系统是实现分布式火控的关键。介绍了在一个小型实时通信系统的设计中,为保证通信的实时性采取了节拍控制、数据分级、重发限制等方法,为提高通信可靠性采用了断路重组技术、差错控制和冗余技术,软件采用了面向对象分层次模块化设计的方法,提高了可维性和可扩展性。通过这些措施,实现了5km距离内数据和语音的多点实时传输,误码率小于10-6,通信时延小于150ms,满足了分布式火控系统的要求。     

一种用于SpaceWire网络的混合路由机制设计*

针对星上系统总线多元性导致的星载网络接口和协议不能标准化的发展瓶颈,本文基于SpaceWire总线协议,通过将静态路由(时间触发)与动态路由(事件触发)机制结合,实现了控制数据和载荷数据共用网络。静态路由完全遵循SpaceWire-D协议,在保证确定性传输的同时,通过启发式调度算法首次实现了多时间窗并行调度,并提出利用最大公约数法设计时间窗,以提高网络吞吐量；动态路由通过对随机事件和载荷数据分配优先级,实现传输路径冲突时对紧急任务的优先处理。最后在OPENT中搭建网络系统仿真模型,对所提出的路由机制进行了仿真。实验结果表明,静态路由时段网络吞吐量较现有调度算法有明显提高,动态路由实现了紧急事件优先传输。