Resilience in peacebuilding: Contesting uncertainty,ambiguity, and complexity

With the failure of liberal peace strategies in the Global South, resilience has recently become the risk management strategy par excellence in peacebuilding. Since it is not possible to predict when the next crisis will take place, peacebuilders must invest in bottom-up adaptive capacities to cope with external shocks. This article moves away from governmentality accounts of resilience which are overtly deterministic and depoliticizing. Instead, it posits that the uncertainty, ambiguity, and complexity associated with resilience mean that we should expect opportunities for contestation and institutional agency. This argument will be illustrated by drawing upon the European Union’s adoption of the resilience approach in its peacebuilding and security policies. The article argues that while uncertainty, ambiguity, and complexity constitute the ontological conditions that underpin the rise of resilience in peacebuilding, they are also likely to lead to its potential demise.     

Mean sojourn times in multiclass feedback queues with gated disciplines

In this paper, we investigate multiclass feedback queues with gated disciplines. The server selects the stations by a nonpreemptive priority scheduling algorithm and serves customers in the selected station by either a gated FCFS discipline or a gated priority discipline. We take a rather systematic approach to their mean sojourn times. We define conditional expected sojourn times for all customers and derive their expressions from an analysis of busy periods. Since they are shown to be linear in some components of the system states, their steady state mean values can be derived from simple limiting procedures. These mean values can be obtained from a set of linear equations. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 719–741, 2003.     

Scheduling jobs with piecewise linear decreasing processing times

We study the problems of scheduling a set of nonpreemptive jobs on a single or multiple machines without idle times where the processing time of a job is a piecewise linear nonincreasing function of its start time. The objectives are the minimization of makespan and minimization of total job completion time. The single machine problems are proved to be NP‐hard, and some properties of their optimal solutions are established. A pseudopolynomial time algorithm is constructed for makespan minimization. Several heuristics are derived for both total completion time and makespan minimization. Computational experiments are conducted to evaluate their efficiency. NP‐hardness proofs and polynomial time algorithms are presented for some special cases of the parallel machine problems. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 531–554, 2003     

The effectiveness of the longest delivery time rule for the flow shop delivery time problem

In the flow shop delivery time problem, a set of jobs has to be processed on m machines. Every machine has to process each one of the jobs, and every job has the same routing through the machines. The objective is to determine a sequence of the jobs on the machines so as to minimize maximum delivery completion time over all the jobs, where the delivery completion time of a job is the sum of its completion time, and the delivery time associated with that job. In this paper, we prove the asymptotic optimality of the Longest Delivery Time algorithm for the static version of this problem, and the Longest Delivery Time among Available Jobs (LDTA) algorithm for the dynamic version of this problem. In addition, we present the result of computational testing of the effectiveness of these algorithms. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

基于遗传算法的自航水雷航路规划

自航水雷在执行任务时需要装载根据战场环境预先规划好的最优路径,路径的优劣直接决定了自航水雷的作战效率.采用遗传算法进行自航水雷航路优化,算法利用极坐标描述威胁位置和航路点,将航路编码由二维缩减至一维,降低了搜索空间,提高了优化效率.对算法进行了相应的仿真,仿真结果表明,编码方式提高了优化效率,得到的航路有效地规避了威胁.     

雷达智能BIT故障预测方法研究

在总结了几种比较常见的故障预测方法的基础上,介绍了基于统计学习理论的支持向量回归算法。提出将智能遗传算法用来对支持向量回归模型的参数进行优化选取,并详细介绍了模型参数的选取过程,避免了参数的盲目设置。将建立起来的模型应用于雷达智能BIT故障预测领域,并以一组智能BIT状态监测的数据对预测模型进行训练和验证,实验结果表明支持向量回归模型能有效地对雷达故障进行预测。     

辛算法应用于Duffing方程的保结构性

讨论了不受外力的Duffing方程在辛算法和非辛算法作用下,相轨线被保持和破坏的性质。证明了当时间步长充分小时,辛算法可以保持原系统的大部分不变闭曲线,而非辛算法却做不到这一点。     

基于探索性计算实验的信息化武器装备体系优化方法

针对信息化武器装备体系复杂系统的结构优化问题,以综合集成思想和复杂自适应系统理论为指导,提出探索性计算实验优化方法和面向探索性计算实验的SABI(System of system,Agent,Behavior,Interaction)建模方法。在分析武器装备体系结构优化目标的基础上,依据武器装备体系探索性计算实验自顶向下的探索分析和自底向上的综合集成分析的要求,给出了武器装备体系结构探索性计算实验优化分析逻辑框架和基于多Agent的武器装备体系探索性计算实验优化分析模型。     

不可能差分分析时间复杂度通用计算公式的改进

研究Boura等和Derbez分别提出的不可能差分分析时间复杂度计算公式,根据实际攻击过程优化密钥排除的步骤,给出不可能差分分析实际攻击的时间复杂度计算的改进公式,进而利用两个分组密码算法模型将改进后公式计算的实际结果分别与Boura等的公式和Derbez的公式的计算结果进行对比,结果表明Boura等的公式计算结果既可能高于优化公式的实际分析计算的结果,也可能低于优化公式的实际分析计算的结果,而在轮子密钥独立时改进后公式的实际计算结果是Derbez公式的计算结果的2-1.2倍。     

Aggregating courier deliveries

We consider the problem of efficiently scheduling deliveries by an uncapacitated courier from a central location under online arrivals. We consider both adversary‐controlled and Poisson arrival processes. In the adversarial setting we provide a randomized (3βΔ/2δ ? 1) ‐competitive algorithm, where β is the approximation ratio of the traveling salesman problem, δ is the minimum distance between the central location and any customer, and Δ is the length of the optimal traveling salesman tour overall customer locations and the central location. We provide instances showing that this analysis is tight. We also prove a 1 + 0.271Δ/δ lower‐bound on the competitive ratio of any algorithm in this setting. In the Poisson setting, we relax our assumption of deterministic travel times by assuming that travel times are distributed with a mean equal to the excursion length. We prove that optimal policies in this setting follow a threshold structure and describe this structure. For the half‐line metric space we bound the performance of the randomized algorithm in the Poisson setting, and show through numerical experiments that the performance of the algorithm is often much better than this bound.