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.     

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.     

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。     

一种有效的优化的多载波通信系统的功率分配算法

本文提出一种关于DMT系统传输纯数据流业务的最佳的功率分配算法，该算法使用了一种有效的表格查手工艺工和拉格朗日乘法器对分搜索办法，能够较快的收敛到最佳的功率点。同时，易于用硬件和软件实现。     

VaR and ES for linear portfolios with mixture of elliptic distributions risk factors

In this paper, we generalize the Linear VaR method from portfolios with normally distributed risk factors to portfolios with mixture of elliptically distributed ones. We treat both the Expected Shortfall and the Value-at-Risk of such portfolios. Special attention is given to the particular case of a mixture of multivariate t-distributions. This is a part of J. SADEFO-KAMDEM PhD Thesis[12] of the Université de Reims, France . It has been presented at the workshop on modelling and computation in Financial Engineering at Bad Herrenalb, Germany May 6-8, 2003. The author is an associate professor at the Department of mathematics, université d’Evry Val d’Essonne.     

Serial deployment of attention during visual search.

This study examined whether objects are attended in serial or in parallel during a demanding visual search task. A component of the event-related potential waveform, the N2pc wave, was used as a continuous measure of the allocation of attention to possible targets in the search arrays. Experiment 1 demonstrated that the relative allocation of attention shifts rapidly, favoring one item and then another. In Experiment 2, a paradigm was used that made it possible to track the absolute allocation of attention to individual items. This experiment showed that attention was allocated to one object for 100-150 ms before attention began to be allocated to the next object. These findings support models of attention that posit serial processing in demanding visual search tasks. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Seeking the truth about ad hoc join costs

In this paper, we re-examine the results of prior work on methods for computing ad hoc joins. We develop a detailed cost model for predicting join algorithm performance, and we use the model to develop cost formulas for the major ad hoc join methods found in the relational database literature. We show that various pieces of “common wisdom” about join algorithm performance fail to hold up when analyzed carefully, and we use our detailed cost model to derive op timal buffer allocation schemes for each of the join methods examined here. We show that optimizing their buffer allocations can lead to large performance improvements, e.g., as much as a 400% improvement in some cases. We also validate our cost model's predictions by measuring an actual implementation of each join algorithm considered. The results of this work should be directly useful to implementors of relational query optimizers and query processing systems. Edited by M. Adiba. Received May 1993 / Accepted April 1996     

山东省水资源配置思路浅析

山东省总体上属于资源性缺水省份，合理配置水资源已成为解决水资源供需矛盾、保障经济社会可持续发展的关键问题之一。通过对山东省水资源的基本特点进行分析，建立了水资源合理配置系统模型及生成配置方案，在供需平衡分析的基础上，提出了水资源合理配置的基本思路。     

An accurate and practical buffer allocation model for the buffer cache based on marginal gains

A new dynamic buffer allocation strategy based on the notion of marginal gains is presented for the buffer cache that is used by the operating system to store frequently accessed disk blocks in main memory, and the performance of the proposed strategy is compared with those of previous allocation strategies. In the proposed strategy, marginal gain values are predicted by exploiting functions that approximate the expected number of buffer hits per unit time. Experimental results from both trace-driven simulation and an actual implementation in the FreeBSD operating system show that the proposed strategy accurately predicts the marginal gain values for various workloads resulting in significantly improved buffer hit ratios.     

Allocation of Scarce Water Resources Using Deficit Irrigation in Rotational Systems

On irrigation schemes with rotational irrigation systems in semiarid tropics, the existing rules for water allocation are based on applying a fixed depth of water with every irrigation irrespective of the crops, their growth stages, and soils on which these crops are grown. However, when water resources are scarce, it is necessary to allocate water optimally to different crops grown in the irrigation scheme taking account of different soils in the command area. Allocating water optimally may lead to applying less water to crops than is needed to obtain the maximum yield. In this paper, a three stage approach is proposed for allocating water from a reservoir optimally based on a deficit irrigation approach, using a simulation-optimization model. The allocation results with a deficit irrigation approach are compared for a single crop (wheat) in an irrigation scheme in India, first with full irrigation (irrigation to fill the root zone to field capacity) and second with the existing rule. The full irrigation with a small irrigation interval was equivalent to adequate irrigation (no stress to the crop). It is found that practicing deficit irrigation enables the irrigated area and the total crop production in the irrigation scheme used for the case study to be increased by about 30–45% and 20–40%, respectively, over the existing rule and by 50 and 45%, respectively, over the adequate irrigation. Allocation of resources also varied with soil types.