基于专家系统的弹道导弹目标识别方法

传统Dempster-Shafer(D-S)算法及其改进算法中,一般将冲突证据与不冲突证据统一融合,无论融合过程中冲突证据所占权重多小,这都将降低融合效率。针对这个问题,引入专家系统理论,面向信息融合中证据冲突的问题,将冲突证据与无冲突证据分组,构建了基于专家信任度的弹道导弹目标识别模型和专家知识库模型,从工程上设计了弹道导弹目标识别专家知识库系统,提出了两种专家知识权重确立方法,并通过实例以及仿真,验证了算法的可行性。     

反导作战多传感器任务规划技术

多传感器任务规划技术是反导作战中的重要研究内容之一,即解决如何发挥多维传感器资源的互补优势,构建"传感器-目标-任务"序列,以实现整体执行效果最优。基于JDL信息融合模型深入剖析了反导作战多传感器任务规划体系结构及其信息交互。在此基础上,结合反导作战特点,从应用和理论研究两个方面分别对多传感器任务规划技术进行了叙述。     

Preemptive parallel‐machine scheduling with a common server to minimize makespan

We consider parallel‐machine scheduling with a common server and job preemption to minimize the makespan. While the non‐preemptive version of the problem is strongly NP‐hard, the complexity status of the preemptive version has remained open. We show that the preemptive version is NP‐hard even if there is a fixed number of machines. We give a pseudo‐polynomial time algorithm to solve the case with two machines. We show that the case with an arbitrary number of machines is unary NP‐hard, analyze the performance ratios of some natural heuristic algorithms, and present several solvable special cases. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 388–398, 2017     

Single machine scheduling with a restricted rate‐modifying activity

In this paper we consider the problem of scheduling a set of jobs on a single machine on which a rate‐modifying activity may be performed. The rate‐modifying activity is an activity that changes the production rate of the machine. So the processing time of a job is a variable, which depends on whether it is scheduled before or after the rate‐modifying activity. We assume that the rate‐modifying activity can take place only at certain predetermined time points, which is a constrained case of a similar problem discussed in the literature. The decisions under consideration are whether and when to schedule the rate‐modifying activity, and how to sequence the jobs in order to minimize some objectives. We study the problems of minimizing makespan and total completion time. We first analyze the computational complexity of both problems for most of the possible versions. The analysis shows that the problems are NP‐hard even for some special cases. Furthermore, for the NP‐hard cases of the makespan problem, we present a pseudo‐polynomial time optimal algorithm and a fully polynomial time approximation scheme. For the total completion time problem, we provide a pseudo‐polynomial time optimal algorithm for the case with agreeable modifying rates. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Manpower allocation with time windows and job‐teaming constraints

In this work, we study manpower allocation with time windows and job‐teaming constraints. A set of jobs at dispersed locations requires teams of different types of workers where each job must be carried out in a preestablished time window and requires a specific length of time for completion. A job is satisfied if the required composite team can be brought together at the job's location for the required duration within the job's time window. The objective is to minimize a weighted sum of the total number of workers and the total traveling time. We show that construction heuristics used with simulated annealing is a good approach to solving this NP‐hard problem. In experiments, this approach is compared with solutions found using CPLEX and with lower bounds obtained from a network flow model. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

Bicriteria scheduling on a single batching machine with job transportation and deterioration considerations

We study a single batching machine scheduling problem with transportation and deterioration considerations arising from steel production. A set of jobs are transported, one at a time, by a vehicle from a holding area to the single batching machine. The machine can process several jobs simultaneously as a batch. The processing time of a job will increase if the duration from the time leaving the holding area to the start of its processing exceeds a given threshold. The time needed to process a batch is the longest of the job processing times in the batch. The problem is to determine the job sequence for transportation and the job batching for processing so as to minimize the makespan and the number of batches. We study four variations (P1, P2, P3, P4) of the problem with different treatments of the two criteria. We prove that all the four variations are strongly NP‐hard and further develop polynomial time algorithms for their special cases. For each of the first three variations, we propose a heuristic algorithm and analyze its worst‐case performance. For P4, which is to find the Pareto frontier, we provide a heuristic algorithm and an exact algorithm based on branch and bound. Computational experiments show that all the heuristic algorithms perform well on randomly generated problem instances, and the exact algorithm for P4 can obtain Pareto optimal schedules for small‐scale instances. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 269–285, 2014     

Proactive release procedures for just‐in‐time job shop environments,subject to machine failures

In this paper, we consider just‐in‐time job shop environments (job shop problems with an objective of minimizing the sum of tardiness and inventory costs), subject to uncertainty due to machine failures. We present techniques for proactive uncertainty management that exploit prior knowledge of uncertainty to build competitive release dates, whose execution improves performance. These techniques determine the release dates of different jobs based on measures of shop load, statistical data of machine failures, and repairs with a tradeoff between inventory and tardiness costs. Empirical results show that our methodology is very promising in comparison with simulated annealing and the best of 39 combinations of dispatch rules & release policies, under different frequencies of breakdowns. We observe that the performance of the proactive technique compared to the other two approaches improves in schedule quality (maximizing delivery performance while minimizing costs) with increase in frequency of breakdowns. The proactive technique presented here is also computationally less expensive than the other two approaches. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

An FPTAS for scheduling a two‐machine flowshop with one unavailability interval

We study a deterministic two‐machine flowshop scheduling problem with an assumption that one of the two machines is not available in a specified time period. This period can be due to a breakdown, preventive maintenance, or processing unfinished jobs from a previous planning horizon. The problem is known to be NP‐hard. Pseudopolynomial dynamic programming algorithms and heuristics with worst case error bounds are given in the literature to solve the problem. They are different for the cases when the unavailability interval is for the first or second machine. The existence of a fully polynomial time approximation scheme (FPTAS) was formulated as an open conjecture in the literature. In this paper, we show that the two cases of the problem under study are equivalent to similar partition type problems. Then we derive a generic FPTAS for the latter problems with O(n⁵/ε⁴) time complexity. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

浅析武警部队职务防卫权

武警部队作为国家武装力量的重要组成部分,职务防卫权有其特殊的性质。从阐述职务防卫与一般正当防卫的区别着手,针对武警行使职务防卫权的客观需求进行分析,并结合当前武警部队行使职务防卫权的现状,对下一步的立法完善提出建议。     

有限维修能力下多级保障系统装备时变可用度评估及保障方案优化

备件库存和站点维修能力是影响备件维修周转的重要因素,制约着装备的使用效果。针对备件需求随任务阶段动态变化时装备保障方案的评估和优化问题,考虑站点维修能力对备件维修过程的影响,结合METRIC建模方法和动态排队理论,建立了有限维修能力下多级保障系统装备时变可用度评估模型。在评估模型基础之上,以保障费用为优化目标、装备可用度为约束条件,建立任务期内多级保障系统保障方案优化模型。以任务期内的最低可用度所对应的备件短缺数为观测值,分析各项资源的边际效益值,采用边际优化算法对各项资源进行优化计算。算例分析表明,评估模型能够计算多级保障系统任务期内各阶段装备可用度;保障方案优化模型和方法能够得到各项保障资源的优化配置方案。提出的模型和优化方法能够为装备保障人员制订合理的保障方案提供决策支持。