A knowledge-based archive multi-objective simulated annealing algorithm to optimize series–parallel system with choice of redundancy strategies

Redundancy allocation problem (RAP) is one of the best-developed problems in reliability engineering studies. This problem follows to optimize the reliability of a system containing s sub-systems under different constraints, including cost, weight, and volume restrictions using redundant components for each sub-system. Various solving methodologies have been used to optimize this problem, including exact, heuristic, and meta-heuristic algorithms. In this paper, an efficient multi-objective meta-heuristic algorithm based on simulated annealing (SA) is developed to solve multi-objective RAP (MORAP). This algorithm is knowledge-based archive multi-objective simulated annealing (KBAMOSA). KBAMOSA applies a memory matrix to reinforce the neighborhood structure to achieve better quality solutions. The results analysis and comparisons demonstrate the performance of the proposed algorithm for solving MORAP.     

移动边缘计算环境下的动态资源分配策略

在通讯设备爆炸式增长的时代,移动边缘计算作为5G通讯技术的核心技术之一,对其进行合理的资源分配显得尤为重要。移动边缘计算的思想是把云计算中心下沉到基站部署(边缘云),使云计算中心更加靠近用户,以快速解决计算资源分配问题。但是,相对于大型的云计算中心,边缘云的计算资源有限,传统的虚拟机分配方式不足以灵活应对边缘云的计算资源分配问题。为解决此问题,提出一种根据用户综合需求变化的动态计算资源和频谱分配算法(DRFAA),采用"分治"策略,并将资源模拟成"流体"资源进行分配,以寻求较大的吞吐量和较低的传输时延。实验仿真结果显示,动态计算资源和频谱分配算法可以有效地降低用户与边缘云之间的传输时延,也可以提高边缘云的吞吐量。     

A self‐scalable load injection service

Load testing of applications is an important and costly activity for software provider companies. Classical solutions are very difficult to set up statically, and their cost is prohibitive in terms of both human and hardware resources. Virtualized cloud computing platforms provide new opportunities for stressing an application's scalability, by providing a large range of flexible and less expensive (pay‐per‐use model) computation units. On the basis of these advantages, load testing solutions could be provided on demand in the cloud. This paper describes a Benchmark‐as‐a‐Service solution that automatically scales the load injection platform and facilitates its setup according to load profiles. Our approach is based on: (i) virtualization of the benchmarking platform to create self‐scaling injectors; (ii) online calibration to characterize the injector's capacity and impact on the benched application; and (iii) a provisioning solution to appropriately scale the load injection platform ahead of time. We also report experiments on a benchmark illustrating the benefits of this system in terms of cost and resource reductions. Copyright © 2013 John Wiley & Sons, Ltd.     

以用户为中心的可见光通信协作传输中训练资源分配算法

以用户为中心的可见光通信协作传输是近年来出现的新架构,这导致虚拟小区之间出现重叠。为避免导频污染问题,每个虚拟小区中的光接入点(AP)或者虚拟小区中选择相同AP的用户发送的训练序列应该是正交的。针对可见光通信中以用户为中心的协作网络,研究训练资源的正交分配问题,提出了一种新的导频分配算法,联合导频分配和用户选择问题,以期最大限度地增加虚拟小区内可被接入的用户数。分析和仿真结果表明,该导频分配方案可以有效改善导频污染问题,提高训练资源利用率,并且相比已有的导频分配方案,性能有所改进。     

Mining fleet management systems: a review of models and algorithms

The objective of this paper is to review and document the mine fleet management systems’ models and algorithms. The purpose is to understand the algorithms behind the fleet management systems and the proposed academic solutions in this area to identify any gaps in the current literature and to open up opportunities to establish research questions that need to be addressed in an integrated simulation and optimisation operational planning research framework. In this paper, we review industrial fleet management systems and the main academic algorithms behind such systems. The fleet management systems are divided into three subsequently related problems to review: shortest path, production optimisation and real-time dispatching. Finally, the limitations of current algorithms for fleet management systems are documented in terms of mining practice feasibility and optimality of the solution on large-scale problems. The results of this literature review enable us to evaluate the logical links between major components of an integrated simulation and optimisation operational planning framework with current theory of fleet management systems.     

基于振动实测的非均质地层钻头失效分析与对策

四川盆地作为国内页岩气开发的重点区域,通过近几年的不断攻关和实践,机械钻速得到了提高,但由于受地层复杂、可钻性差、非均质性强等地质因素的影响,导致井下钻柱系统不良振动剧烈,容易出现钻头损坏严重、钻速较低等问题,严重影响了钻井时效。为了解决上述难题,以该盆地涪陵工区上二叠统龙潭组—中二叠统茅口组为例,采用井下振动高频测量工具的实测手段,测量了钻头—钻柱系统的动态振动加速度参数,结合地层的岩性和矿物组分分析,研究钻头失效原因与对策,并开展了现场试验。研究结果表明:①在非均质地层中钻进的钻头—钻柱系统产生了大于40 m/s~2的高幅值瞬时冲击振动,高幅值的瞬时冲击是导致钻头先期失效的主要原因;②提出了抑制高幅值的瞬时冲击振动采用"减振+增压"工具组合和避免井下工具共振的钻井参数;③采用钻井新参数的试验井比邻井的高幅值瞬时振动降低了17%,单只钻头进尺增加24%,钻头工作环境得到了较大的改善,钻头使用数量减少。结论认为,该研究成果能够有效地改善钻头—钻柱系统的振动状态,有利于达成延长钻头使用寿命的目标。     

流域泥沙灾害与泥沙资源性的研究

泥沙灾害与泥沙资源性是流域泥沙的重要属性,二者在一定条件下可以相互转化。本文论述了泥沙淤积、泥沙冲刷、岸滩崩塌、山地崩塌与泥石流、粗沙淤积的土地沙化等泥沙灾害,指出泥沙灾害具有时空分布的不均匀性、渐变性或突发性、群发性、转化性及危害严重性等;流域泥沙资源化的主要途径包括填海造陆及造地、引洪淤灌、堤防淤临淤背、建筑材料、湿地形成(河流、湖泊与河口海岸)等,指出流域泥沙资源化及其优化配置既要解决思想观念、基本理论、目标效益等方面的问题,还要考虑与水资源联合配置问题。     

随钻扩眼工具及技术研究

基于随钻扩眼技术优势的分析，研究了机械式、液压式和偏心式随钻扩眼工具执行机构和扩眼总成的机构原理，并介绍了国内所开展的相关研究。文章提出应加强现有工具的适应性和匹配性研究，发掘各类工具的优势。优化执行机构、扩眼总成和水力机构、重视底部钻具组合力学特性的分析是今后发展和完善随钻扩眼工具及技术的几个重要内容。实践表明，随钻扩眼技术在处理井下复杂情况、降低钻井综合成本、提高钻井速度、提高建井质量和安全性等方面具有显著的优势，随钻扩眼工具也正逐渐成为一种重要的石油钻井配套工具。     

PDC钻头水力结构优化设计研究

在PDC钻头工作过程中，钻井液对钻头体表面的冲洗、冷却和润滑是保证钻头正常工作的一个非常重要的条件。对PDC钻头而言，水力结构（主要是中心水眼和冠部水道）设计的重要性尤其突出。以前,对钻头水力系统研究只能通过实验的方法进行,研究周期长、成本高、结构调整不方便，而数值模拟的方法在几年前还不成熟，甚至静态的复杂结构流场问题基本无法解决。为此，在提出PDC钻头水力结构优化设计原则的基础上，对PDC钻头的三维流场进行了数值模拟。模拟中考虑了钻头的喷嘴布置位置、直径、数量以及切削齿对流场的影响。计算结果表明，原设计在喷嘴布置位置和喷射角度上存在不足，以此为基础进行了水力结构的优化设计。文中的研究成果成功地应用在新型钻头水力结构的设计中，研究方法为PDC钻头水力结构优化分析奠定了理论基础。     

随机库存分配问题的一种求解方法

讨论了在VMI管理思想下对具有随机需求特性的多客户库存分配问题 ,重点论述了有效近似算法的设计过程 ,最后基于一组模拟数据给出了一个算例。