超算环境科学工作流应用的容错

超算环境中科学工作流技术广泛应用于科学研究和工程仿真领域。复杂多物理过程数值模拟、多阶段数据处理等应用往往需要使用多种应用软件相互协作,构建业务流程自动执行来提升工作效率。然而在超算环境中执行科学工作流应用面临着资源失效、任务配置错误等异常情况,造成工作流执行中断,严重影响完成效率,故容错功能对超算工作流应用的稳定持续运行有重要意义。介绍了科学工作流的容错设计分类,并对典型工作流系统的容错设计进行分析评述;提出了基于决策树的事件-条件-动作容错模型,设计了非侵入式可扩展的容错架构,并针对自主研发的部署在超算环境下的科学工作流应用平台HSWAP,实现了运行时可配置的容错策略。在实际的工程仿真任务中,基于所提出模型和架构实现的容错机制为提高工作流执行效率发挥了重要作用。     

舰艇编队作战系统的武器目标分配问题

设我方m艘战舰,对方n个来袭目标.运用灰色局势决策求得目标对各个战舰产生的威胁值排序;再用模拟退火算法,参考目标威胁,单舰根据自身装载的火力发射进行初步武器分配;最后将分配结果传送至融合中心,应用大系统理论的分解协调法,协调武器分配,使得我方武器对本批目标的打击概率最大.仿真基于VC++编程实现,具体分析了算法及思想的可行性.     

Client‐contractor bargaining on net present value in project scheduling with limited resources

The client‐contractor bargaining problem addressed here is in the context of a multi‐mode resource constrained project scheduling problem with discounted cash flows, which is formulated as a progress payments model. In this model, the contractor receives payments from the client at predetermined regular time intervals. The last payment is paid at the first predetermined payment point right after project completion. The second payment model considered in this paper is the one with payments at activity completions. The project is represented on an Activity‐on‐Node (AON) project network. Activity durations are assumed to be deterministic. The project duration is bounded from above by a deadline imposed by the client, which constitutes a hard constraint. The bargaining objective is to maximize the bargaining objective function comprised of the objectives of both the client and the contractor. The bargaining objective function is expected to reflect the two‐party nature of the problem environment and seeks a compromise between the client and the contractor. The bargaining power concept is introduced into the problem by the bargaining power weights used in the bargaining objective function. Simulated annealing algorithm and genetic algorithm approaches are proposed as solution procedures. The proposed solution methods are tested with respect to solution quality and solution times. Sensitivity analyses are conducted among different parameters used in the model, namely the profit margin, the discount rate, and the bargaining power weights. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

Information security: Designing a stochastic‐network for throughput and reliability

Todas information and communication network requires a design that is secure to tampering. Traditional performance measures of reliability and throughput must be supplemented with measures of security. Recognition of an adversary who can inflict damage leads toward a game‐theoretic model. Through such a formulation, guidelines for network designs and improvements are derived. We opt for a design that is most robust to withstand both natural degradation and adversarial attacks. Extensive computational experience with such a model suggests that a Nash‐equilibrium design exists that can withstand the worst possible damage. Most important, the equilibrium is value‐free in that it is stable irrespective of the unit costs associated with reliability vs. capacity improvement and how one wishes to trade between throughput and reliability. This finding helps to pinpoint the most critical components in network design. From a policy standpoint, the model also allows the monetary value of information‐security to be imputed. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

消防部队处置生物突发事件辅助决策系统构建

阐述了生物突发事件的重大危害性和建立生物突发事件辅助决策系统的主要目的和意义。从生物突发事件应急救援工作的实际需求出发，对辅助决策系统软件的设计进行了研究，应用Access数据库和VB6．0，编制出消防部队处置生物突发事件辅助决策系统，并对该软件的相关功能进行了必要的说明。     

Maximizing deviation method for multiple attribute decision making under q-rung orthopair fuzzy environment

Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment, the evaluation information of alternatives given by decision makers is often fuzzy and uncertain. As a generalization of intuitionistic fuzzy set (IFSs) and Pythagoras fuzzy set (PFSs), q-rung orthopair fuzzy set (q-ROFS) is more suitable for expressing fuzzy and uncertain information. But, in actual multiple attribute decision making (MADM) problems, the weights of DMs and attributes are always completely unknown or partly known, to date, the maximizing deviation method is a good tool to deal with such issues. Thus, combine the q-ROFS and conventional maximizing deviation method, we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper. Firstly, we briefly introduce the basic concept of q-rung orthopair fuzzy sets (q-ROFSs) and q-rung interval-valued orthopair fuzzy sets (q-RIVOFSs). Then, combine the maximizing deviation method with q-rung orthopair fuzzy information, we establish two new decision making models. On this basis, the proposed models are applied to MADM problems with q-rung orthopair fuzzy information. Compared with existing methods, the effectiveness and superiority of the new model are analyzed. This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers (q-ROFNs) and whose attributes are incomplete.     

防空兵指挥决策系统及其运行环境的影响

决策者、决策辅助人员和指挥决策信息系统是部队指挥决策系统的基本组成部分,防空兵指挥自动化和决策支持系统则是指挥决策信息系统的一部分,环境因素和决策信息是影响防空兵指挥决策系统的重要因素.从系统的观点阐述了防空兵指挥决策系统与内外环境因素的关系,提出在新技术条件下,系统信息是防空兵指挥决策系统的又一组成要素.从这个观点出发,可以准确、全面地了解和分析系统环境因素对防空兵指挥决策系统影响,最终达到提高防空兵指挥决策效能的目的.     

基于Epsilon-Nash策略的动态武器-目标分配方法

在大型任务规划软件的作战单元任务分配中,搜索零和博弈问题的纳什均衡点是求解任务分配的一种有效的方法。然而,纳什均衡点在决策中并不一定总是存在且唯一,这造成了纳什均衡策略在实际使用时具有较大的局限。通过采用Epsilon-Nash策略克服这种局限,并将其应用于自主空战任务规划系统中,通过仿真实验,证实Epsilon-Nash策略具有近似于纳什策略的效果。     

基于系统动力学的协同决策模型性能分析

为探索信息化作战中指挥控制关键因素，提出改进作战指挥体制的对策措施，采用系统动力学理论，对协同决策的结构、参与者和信息反馈关系等关键因素进行了分析，在此基础上构建了基于系统动力学的协同决策模型并进行了模拟仿真。结果表明，增加指挥控制机构之间的信息共享可以有效提升协同决策的效率，为建立协同决策指挥控制体制提供了借鉴意义。     

Energy‐efficient scheduling for sustainable manufacturing systems with renewable energy resources

Environmentally friendly energy resources open a new opportunity to tackle the problem of energy security and climate change arising from wide use of fossil fuels. This paper focuses on optimizing the allocation of the energy generated by the renewable energy system to minimize the total electricity cost for sustainable manufacturing systems under time‐of‐use tariff by clipping the peak demand. A rolling horizon approach is adopted to handle the uncertainty caused by the weather change. A nonlinear mathematical programming model is established for each decision epoch based on the predicted energy generation and the probability distribution of power demand in the manufacturing plant. The objective function of the model is shown to be convex, Lipchitz‐continuous, and subdifferentiable. A generalized benders decomposition method based on the primal‐dual subgradient descent algorithm is proposed to solve the model. A series of numerical experiments is conducted to show the effectiveness of the solution approach and the significant benefits of using the renewable energy resources.