复杂网络影响力极大化快速评估算法

分析复杂网络中影响力极大化问题，设计一种新的启发式算法框架。针对信息传递中节点的交互方式进行分析，给出节点在任意时刻处于信息接收态的概率。通过期望计算得到种子节点集传播影响力的近似估计，实现集群影响力快速计算，进而得到基于序列采样的影响力极大化快速评估算法。特别地，对于六个来自不同领域的真实网络上的影响力极大化问题进行了研究，仿真结果表明：该方法能够高效识别网络中具有重要传播影响力的节点集，在三种常见度量准则下的表现均明显优于三种影响力极大化问题基准算法。     

装备维修器材生产路径决策的两阶启发式算法

当前装备供应保障系统中维修器材存在短缺、积压以及配送系统效率低下等问题,亟须对生产、库存和配送作业环节进行集成优化。为客观反映各个决策环节,将该问题公式化为一个混合整数线性规划模型,针对该模型多变量、多约束的特点,提出了一个基于数学规划的两阶启发式算法对其进行求解。结合算例,检验模型的可行性,并选取求解器CPLEX和一个类似的迭代算法与该算法在求解质量和运算时间方面进行对比与分析。结果表明,提出的模型是合理可行的,该算法在求解不同规模实例时表现出优异的性能。     

关联规则挖掘在发动机故障分析中的应用

大部分关联规则挖掘算法仅以出现频率作为阈值来产生关联规则,然而在发动机故障数据分析领域,很多关键故障的出现机率较低,采用传统的挖掘算法无法适应航空发动机故障分析的需要.提出一种新算法,称为权重式多重支持度关联规则挖掘算法,此算法可针对不同重要度的故障定出不同的支持度阈值,由此产生的关联规则,可以解决高重要度但出现较少的故障不易被挖掘的问题.     

Optimizing barge utilization in hinterland container transportation

In hinterland container transportation the use of barges is getting more and more important. We propose a real‐life operational planning problem model from an inland terminal operating company, in which the number of containers shipped per barge is maximized and the number of terminals visited per barge is minimized. This problem is solved with an integer linear program (ILP), yielding strong cost reductions, about 20%, compared to the method used currently in practice. Besides, we develop a heuristic that solves the ILP in two stages. First, it decides for each barge which terminals to visit and second it assigns containers to the barges. This heuristic produces almost always optimal solutions and otherwise near‐optimal solutions. Moreover, the heuristic runs much faster than the ILP, especially for large‐sized instances.     

Mathematical formulation and heuristic algorithm for the block relocation and loading problem

This study considers the block relocation and loading problem in container terminals. The optimal loading sequence and relocation location are simultaneously decided on the basis of the desired ship‐bay and initial yard space configuration. An integer linear programming model is developed to minimize the number of relocations in the yard space on the basis of no shifts in the ship bay. The accuracy of the model is tested on small‐scale scenarios by using CPLEX. Considering the problem size in the real world, we present a rule‐based heuristic method that is combined with a mathematical model for the removal, loading, and relocation operations. The influence of rules on algorithm performance is also analyzed, and the heuristic algorithm is compared with different types of algorithms in the literature. The extensive numerical experiments show the efficiency of the proposed heuristic algorithm.     

Conceptualizing caveats for political research: Defining and measuring national reservations on the use of force during multinational military operations

The upsurge in post-Cold War coalition operations has stimulated research on caveats: national reservations on the use of force in multinational military operations. However, because the concept of caveats has no agreed-upon definition, it is used inconsistently. This in turn impedes comparing research findings across academic and policy studies and therefore systematic research. This article is a contribution to the scholarly debate on how the analytical concept of caveats are to be delimited. Crucially, we argue that caveats result from some calculated political decision, and should not be confused with reserved behavior due to financial and technical limitations, or lack of coordination. We suggest that caveats are empirically observed and measured in two ways: First, we argue that coalition rules of engagement should be used as a yardstick for measuring direct reservations on the use of force. Second, we suggest reservations on task-assignment and geographical mobility should be used to register indirect reservations.