基于模糊综合决策的航迹相关算法

引用模糊综合决策的思想,提出一种新的分布式航迹相关算法．文中论述了多因素模糊综合评判的基本模型,详细讨论了合成运算模型的选择,重点研究了模糊综合航迹关联准则,并通过仿真将它与两种经典方法进行了比较．仿真结果表明,在密集目标环境下和／或交叉、分岔及机动航迹较多的场合,模糊航迹关联算法的性能明显优于传统方法,其正确关联率比传统方法提高了大约35％．     

利用主观数据建立维修模型

给出了在维修建模过程中用三个状态描述设备状态时,利用主观数据和客观数据建立维修模型的程序、方法和示例,所给方法可直接用于实际问题的建模。     

坦克分队火力指挥理论研究

基于数理战术学理论,研究坦克分队最优火力运用策略问题,所得到的结论符合坦克分队作战的特点,为坦克分队辅助指挥决策系统的研究打下基础。     

装甲车辆维修质量管理研究

结合维修改革试验试行资料和当前部队在维修方面存在的不足,从硬件和软件两部分,分析装甲车辆维修质量存在的问题及影响因素,提出加强维修理论教育,完善维修工艺标准,完善维修配套设施与设备,建立维修质量评估标准和数据信息系统的措施.     

武器系统的故障诊断方式及其模糊决策

文中提出了多种用于单级或多级的实时诊断方式,并采用模糊决策法对其进行优化选择。为新型武器系统故障诊断装置的总体方案设计,提供了一定的依据。     

关于美军综合后勤保障的综述

综合后勤保障是美军武器系统研制与采办过程的一项重要活动,本文阐述了这一活动的基本概念、实质内容、发展动态以及对我军的启示。     

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     

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。     

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     

Minimizing the false alarm rate in systems with transient abnormality

We consider a stochastic partially observable system that can switch between a normal state and a transient abnormal state before entering a persistent abnormal state. Only the persistent abnormal state requires alarms. The transient and persistent abnormal states may be similar in appearance, which can result in excess false alarms. We propose a partially observable Markov decision process model to minimize the false alarm rate, subject to a given upper bound on the expected alarm delay time. The cost parameter is treated as the Lagrange multiplier, which can be estimated from the bound of the alarm delay. We show that the optimal policy has a control‐limit structure on the probability of persistent abnormality, and derive closed‐form bounds for the control limit and present an algorithm to specify the Lagrange multiplier. We also study a specialized model where the transient and persistent abnormal states have the same observation distribution, in which case an intuitive “watchful‐waiting” policy is optimal. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 320–334, 2016