基于案例决策理论的仿真任务共同体服务选择算法

资源分配优化是面向服务（ SOA）的大型多用途仿真系统的关键问题,而含有不确定状态或效果的服务选择是资源分配优化中的一个难点。针对以上问题,提出了构建仿真任务共同体的方法,基于案例的决策理论（ CBDT）的思想,设计了一种不确定型仿真任务共同体服务选择算法（ CBDSSA）。算法通过服务选择案例相似度的层次化运算,生成相似历史案例集,计算得到相似历史案例的方案效用值,最终评估出目标服务选择方案综合效用值并排序备选。算例验证表明,算法约束条件少,层次结构分明,运算结果直观,为仿真任务共同体服务选择问题提供了一种新的思路和实践手段,对大型多用途仿真系统资源分配优化研究具有一定的参考价值。     

基于混合粒子群优化的多目标决策新方法

多目标优化问题中的一个关键在于合理地评判各有效解的优劣。通过引入灰色系统理论中灰色关联度的概念作为评判准则,结合粒子群优化算法进行有约束多目标规划问题的研究。提出了一种新的不可行解的保留策略,进化过程中以此策略保留适量的不可行解,有利于增强对约束边界附近可能的最优解的搜索,同时,针对粒子群优化算法的容易陷入局部最优的缺点,实现了以粒子群优化为载体的混合算法:即对全局极值邻域进一步混沌搜索寻优。仿真结果表明改进的算法对多目标决策问题是有效的。     

基于SD方法的作战指挥决策系统效能分析模型

指挥决策系统是一个非线性的复杂系统,用一般的解析方法难以对其进行效能评估。在分析指挥决策系统构成的基础上,根据指挥决策的4个要素,建立了指挥决策系统的评估指标体系;综合考虑战术和技术指标,从指挥员影响度,指挥机关影响度,指挥信息系统影响度和决策信息影响度4个方面建立了指挥决策系统效能分析模型,前两项指标可以采用层次分析法等方法确定其效能值,后两项指标利用系统动力学方法,结合实际作战的具体战术指标建模,实现了效能值的动态评估分析。     

Dynamic coordination of production planning and sales admission control in the presence of a spot market

We consider the decision‐making problem of dynamically scheduling the production of a single make‐to stock (MTS) product in connection with the product's concurrent sales in a spot market and a long‐term supply channel. The spot market is run by a business to business (B2B) online exchange, whereas the long‐term channel is established by a structured contract. The product's price in the spot market is exogenous, evolves as a continuous time Markov chain, and affects demand, which arrives sequentially as a Markov‐modulated Poisson process (MMPP). The manufacturer is obliged to fulfill demand in the long‐term channel, but is able to rein in sales in the spot market. This is a significant strategic decision for a manufacturer in entering a favorable contract. The profitability of the contract must be evaluated by optimal performance. The current problem, therefore, arises as a prerequisite to exploring contracting strategies. We reveal that the optimal strategy of coordinating production and sales is structured by the spot price dependent on the base stock and sell‐down thresholds. Moreover, we can exploit the structural properties of the optimal strategy to conceive an efficient algorithm. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Optimal control of a production‐inventory system with both backorders and lost sales

We consider the optimal control of a production inventory‐system with a single product and two customer classes where items are produced one unit at a time. Upon arrival, customer orders can be fulfilled from existing inventory, if there is any, backordered, or rejected. The two classes are differentiated by their backorder and lost sales costs. At each decision epoch, we must determine whether or not to produce an item and if so, whether to use this item to increase inventory or to reduce backlog. At each decision epoch, we must also determine whether or not to satisfy demand from a particular class (should one arise), backorder it, or reject it. In doing so, we must balance inventory holding costs against the costs of backordering and lost sales. We formulate the problem as a Markov decision process and use it to characterize the structure of the optimal policy. We show that the optimal policy can be described by three state‐dependent thresholds: a production base‐stock level and two order‐admission levels, one for each class. The production base‐stock level determines when production takes place and how to allocate items that are produced. This base‐stock level also determines when orders from the class with the lower shortage costs (Class 2) are backordered and not fulfilled from inventory. The order‐admission levels determine when orders should be rejected. We show that the threshold levels are monotonic (either nonincreasing or nondecreasing) in the backorder level of Class 2. We also characterize analytically the sensitivity of these thresholds to the various cost parameters. Using numerical results, we compare the performance of the optimal policy against several heuristics and show that those that do not allow for the possibility of both backordering and rejecting orders can perform poorly.© 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

AHP-SWOT分析法在控制下交付行动方案决策中的应用

控制下交付作为打击毒品犯罪尤其是跨国有组织毒品犯罪的重要措施和手段,已发挥越来越重要的作用,是其他缉毒措施和手段无法取代的。但是,由于毒品犯罪的集团化、国际化、种类多元化程度加剧,使得控制下交付的复杂性与不确定性越来越明显。鉴于此,将AHP植入SWOT分析法中,以定性和定量相结合的科学方法解决控制下交付行动方案的优选问题,对提高控制下交付的成功率具有重要意义。     

军事攻防中的多属性资源分配对策模型

针对资源受限情形下的两阶段攻防资源分配问题,提出一种基于多属性决策的资源分配对策模型。防守者首先将有限的防护资源分配到不同的目标上,继而进攻者选择一种威胁组合方式对目标实施打击。基于博弈论相关知识,模型的求解结果可以使防守者最小化自身损失,使进攻者最大化进攻收益。同时,针对模型的特点,给出了一些推论和证明。通过一个示例验证了模型的合理性以及相关推论的准确性,能够为攻、防双方规划决策提供辅助支持。     

基于DW+OLAP+DM的器材保障决策支持系统设计

针对我军当前器材保障状况,阐述了基于数据仓库、联机分析处理和数据挖掘技术的决策支持系统的设计方案和开发理论。通过分析器材保障决策支持的特点,确定了器材保障决策支持系统的需求。具体论述了器材保障决策支持系统的设计步骤,重点讨论了数据仓库多维数据结构的设计。     

装备战斗恢复力模糊评判模型的建立与应用

针对装备战斗恢复力的评价具有随机性、模糊性和相关性的特点 ,提出了用模糊评判模型分析装备战斗恢复力的方法。最后 ,以雷达系统为例 ,对该模型进行了应用分析     

普通物理实验CAI的制作设想

普通物理学实验是公共必修课,随着电子技术迅速发展,多媒体已被广泛的运用,使人机交互能力大大提高,它正作为一种重要的教学媒体迅速应用于教学过程中,对促进教学现代化起着十分重要的作用.因此,制作CAI课件使学生由被动学习变主动学习,并能加深学生对实验内容的理解,对实验现象的观察和规范学生的实验操作技能,从而达到有效提高教学质量和教学效率的目的.