A fuzzy-QFD approach to supplier selection

This article suggests a new method that transfers the house of quality (HOQ) approach typical of quality function deployment (QFD) problems to the supplier selection process. To test its efficacy, the method is applied to a supplier selection process for a medium-to-large industry that manufactures complete clutch couplings.The study starts by identifying the features that the purchased product should have (internal variables “WHAT”) in order to satisfy the company's needs, then it seeks to establish the relevant supplier assessment criteria (external variables “HOW”) in order to come up with a final ranking based on the fuzzy suitability index (FSI). The whole procedure was implemented using fuzzy numbers; the application of a fuzzy algorithm allowed the company to define by means of linguistic variables the relative importance of the “WHAT”, the “HOW”–“WHAT” correlation scores, the resulting weights of the “HOW” and the impact of each potential supplier.Special attention is paid to the various subjective assessments in the HOQ process, and symmetrical triangular fuzzy numbers are suggested to capture the vagueness in people's verbal assessments.     

A neural network based reputation bootstrapping approach for service selection

With the concept of service-oriented computing becoming widely accepted in enterprise application integration, more and more computing resources are encapsulated as services and published online. Reputation mechanism has been studied to establish trust on prior unknown services. One of the limitations of current reputation mechanisms is that they cannot assess the reputation of newly deployed services as no record of their previous behaviours exists. Most of the current bootstrapping approaches merely assign default reputation values to newcomers. However, by this kind of methods, either newcomers or existing services will be favoured. In this paper, we present a novel reputation bootstrapping approach, where correlations between features and performance of existing services are learned through an artificial neural network (ANN) and they are then generalised to establish a tentative reputation when evaluating new and unknown services. Reputations of services published previously by the same provider are also incorporated for reputation bootstrapping if available. The proposed reputation bootstrapping approach is seamlessly embedded into an existing reputation model and implemented in the extended service-oriented architecture. Empirical studies of the proposed approach are shown at last.     

采用改进遗传算法的变压器优化设计

电力机车变压器的优化设计,采用遗传算法是比较好的选择,但传统遗传算法存在一些弊端,文章从编码方式、遗传操作等几个方面探讨了如何对其进行改进,并使用Visual C++编写了一套设计软件,实践证明这种改进是有效的。     

A genetic algorithm for the partial binary constraint satisfaction problem: an application to a frequency assignment problem

We describe a genetic algorithm for the partial constraint satisfaction problem. The typical elements of a genetic algorithm, selection, mutation and cross-over, are filled in with combinatorial ideas. For instance, cross-over of two solutions is performed by taking the one or two domain elements in the solutions of each of the variables as the complete domain of the variable. Then a branch-and-bound method is used for solving this small instance. When tested on a class of frequency assignment problems this genetic algorithm produced the best known solutions for all test problems. This feeds the idea that combinatorial ideas may well be useful in genetic algorithms.     

Classification of spammer and nonspammer content in online social network using genetic algorithm-based feature selection

ABSTRACT

The emergence of online social network invokes social actors to share their personal information digitally. Moreover, it provides the facility to maintain their links with people of same interest globally. Take advantage of these services; it has become a fascinating testbed to invite various threats like a spammer. Detection of spammer in OSN is one of the most critical tasks. Spammer not only spreads unwanted or bad advertisement but does certain malicious activity in others' profiles. By clearly understanding the activities of different threats, some incremental and accurate approaches are needed for detecting spammer content and profiles involved in these activities by using social network services. Therefore, the focus of this article is to detect spammer content and account, specifically on the leading microblogging platform called Twitter. We propose a hybrid approach which leverages the capabilities of various machine learning algorithms to separate spammer and nonspammer contents and account. Initially, the optimisation algorithm called genetic algorithm analyses the various features and selects the best suitable features that influence the behaviour of user account, and these features are then used to train classifiers. Our framework achieved to severalise spammer and nonspammer content in an effective way. Finally, to prove the efficiency of our proposed framework, a comparative analysis is conducted with some existing state-of-art techniques. The experimental analysis shows that our approach achieves a high detection rate of 99.6%, which is better than other state-of-art techniques.     

A context-based service matching approach towards functional reliability for industrial systems

ABSTRACT

As service-oriented computing is commonly used in industrial systems to deal with the continually changing business environment, matching processes with existing services becomes one of the most important phases in constructing, integrating and optimizing information systems. The precision of semantic service matching becomes a critical factor in ensuring the correctness of functionalities in system processes. However, the dependability of semantic service matching cannot be warranted in complex contexts. To improve semantic service matching for industrial systems, a context-based semantic service matching approach named ‘Process-Based service MatchMaker’(PBMM) is proposed in this paper. It selects the suitable services for the process from candidate services through taking the dependencies of related services process into consideration.     

A new three-dimensional manufacturing service composition method under various structures using improved Flower Pollination Algorithm

With the growing complexity of customer requirements and the increasing scale of manufacturing services, how to select and combine the single services to meet the complex demand of the customer has become a growing concern. This paper presents a new manufacturing service composition method to solve the multi-objective optimization problem based on quality of service (QoS). The proposed model not only presents different methods for calculating the transportation time and transportation cost under various structures but also solves the three-dimensional composition optimization problem, including service aggregation, service selection, and service scheduling simultaneously. Further, an improved Flower Pollination Algorithm (IFPA) is proposed to solve the three-dimensional composition optimization problem using a matrix-based representation scheme. The mutation operator and crossover operator of the Differential Evolution (DE) algorithm are also used to extend the basic Flower Pollination Algorithm (FPA) to improve its performance. Compared to Genetic Algorithm, DE, and basic FPA, the experimental results confirm that the proposed method demonstrates superior performance than other meta heuristic algorithms and can obtain better manufacturing service composition solutions.     

Green supplier selection: a new genetic/immune strategy with industrial application

With the onset of the ‘climate change movement’, organisations are striving to include environmental criteria into the supplier selection process. This article hybridises a Green Data Envelopment Analysis (GDEA)-based approach with a new Genetic/Immune Strategy for Data Envelopment Analysis (GIS-DEA). A GIS-DEA approach provides a different view to solving multi-criteria decision making problems using data envelopment analysis (DEA) by considering DEA as a multi-objective optimisation problem with efficiency as one objective and proximity of solution to decision makers’ preferences as the other objective. The hybrid approach called GIS-GDEA is applied here to a well-known automobile spare parts manufacturer in India and the results presented. User validation developed based on specific set of criteria suggests that the supplier selection process with GIS-GDEA is more practical than other approaches in a current industrial scenario with multiple decision makers.     

浅谈提高电子化信息企业服务水平的对策

文章根据我国电子化信息企业的发展现状,分析了发展中存在的一些问题和不足,提出了加快发展,提高服务水平的对策。     

我国现代服务业发展现状与路径选择

现代服务业是衡量一个国家和地区经济发展水平的重要标志,其具有的资源消耗低、环境污染少等产业特点正契合了当前发展低碳经济的要求。低碳背景下,加快发展现代服务业无疑是推动我国当前产业结构优化升级、转变经济发展方式的有力举措。文章概述了我国现代服务业的发展现状,并对现代服务业发展存在的问题进行了评析,在此基础上勾画了我国现代服务业的发展路径。     

A goal-seeking approach to capital budgeting

This paper articulates how a goal-seeking model addresses a variation of the capital-budgeting problem. Focused toward technology modernization in the public sector, this multi-criteria optimization model explicitly considers the diverse functions of the organization. In particular, the synergism amongst the functions is modeled as a multiplicative value function. The model is solved by the “constraint reduced feasible-region method”, resulting in a non-convex mathematical program that produces numerical intricacies. Linearization of the criterion (objective) functions reduces such intricacy. An Army-modernization acquisition-study was used to illustrate the proposed model, showing that its non-inferior solutions are remarkably stable. Comparison is also made with other approaches, typically formulated as goal-setting programs. The model highlights how technology acquisitions are affected as the priorities of each organizational function changes.     

Measuring the impact of the approach to migration in the quality of web service interfaces

There is a good consensus on the strategic value of service-oriented architecture (SOA) as a way of structuring systems, and a common trend is to migrate legacy applications that use outdated technologies and architectures to SOA. We study the effects in the resulting Web Service interfaces of applying two traditional migration approaches combined with common ways of building services, namely, direct migration with code-first and indirect migration with contract-first. The migrated system was a 35-year-old COBOL system of a government agency that serves several millions of users. In addition, we provide a deep explanation of the trade-offs involved in following either combinations. Results confirm that the ‘fast and cheap’ approach to move into SOA, which is commonplace in the industry, may deliver poor service interfaces, and interface quality is also subject to the tools supporting the migration process.     

货物配装和车辆路径问题的一种联合求解方法

货物配装和车辆路径问题(VRP)都是NP难问题,启发式算法是求解此类问题的常用方法。求解单配送中心多车型的货物配送问题,需要改进传统遗传算法:首先采用双层结构表示染色体,车辆数无需事先确定;然后对随机产生的客户序列,利用三叉树算法进行货物配装确定每辆车的配装方案,从而可以知道每个客户的货物装车顺序;依据先装后卸的原则,可得每辆车的客户装车顺序的逆序便是每辆车的客户配送顺序;最终得到货物配装方案和配送方案。基于此思想,通过Java编程验证了一个实例,证明算法切实可行,对实际作业有一定借鉴作用。     

A Huff model with firm heterogeneity and selection. Application to the Italian retail sector

ABSTRACT

In this paper, firm heterogeneity (in terms of productivity, i.e., marginal costs) is incorporated into a Huff model of competition in the Italian retail sector. A higher market potential in the trade area is associated with higher average productivity and lower productivity dispersion through selection of the best stores. The analysis, based on a unique data set encompassing 14,212 Italian retailers, finds support for this relationship in Southern Italy, but not in Northern and Central Italy (where opposite results are obtained in some cases), suggesting the selection dynamics are affected by context factors (other than provincial/regional accessibility) related to an upper geographical scale. The results are robust to controlling for local context factors such as financial risk and floor size restrictions. Floor size restrictions are found to enhance selection.     

保险公司违规支付代理手续费探析

在办理个人住房抵押贷款保险中,保险公司违规支付高额代理手续费已成为保险业的普遍现象。文章基于对个人住房抵押贷款的审计实践,揭示了保险公司违规支付代理手续费的常见手法,并对其成因进行了深层次的分析,以此提出政策建议。     

构建最小入侵检测特征集的贪心算法

文章通过贪心算法构建入侵检测特征串的最小特征集,并生成基于该最小特征集的确定有限状态自动机(DFA)。实验结果表明:该方法减少入侵检测特征的存储空间40%,提高了基于DFA模式匹配的入侵检测速度,有效提升了入侵检测软硬件系统的性能。     

A two–stage approach to additive time series models

For nonlinear additive time series models, an appealing approach used in the literature to estimate the nonparametric additive components is the projection method. In this paper, it is demonstrated that the projection method might not be efficient in an asymptotic sense. To estimate additive components efficiently, a two–stage approach is proposed together with a local linear fitting and a new bandwidth selector based on the nonparametric version of the Akaike information criterion. It is shown that the two–stage method not only achieves efficiency but also makes bandwidth selection relatively easier. Also, the asymptotic normality of the resulting estimator is established. A small simulation study is carried out to illustrate the proposed methodology and the two–stage approach is applied to a real example from econometrics.     

一种基于遗传算法求解车间调度问题的优化方法

遗传算法是解决车间调度问题的有效方法之一。但在构造适应度函数时由于调度问题诸多的束条件使得直接求解十分困难。罚函数法将约束条件加到目标函数上，变有约束为无约束．能较易求解该类问题。     

浅谈电流、电压互感器的选择对保护测量回路的影响

随着电力基础设施建设的日趋完善,以及电力技术研究和应用的不断加强,我国现已基本构建了具有安全性、稳定性特征的电力供应和传输系统,为社会经济的发展及人们的日常生活提供了稳定的电力能源供应。在电力系统的构建与管理中,电流、电压互感器对于实现继电保护功能具有重大的意义,其二次参数和测量表计的特性与继电保护相符合。电磁式模式是传统继电保护装置的基础形态,其主要特点是模拟量输入、精度低、耗电量大,因此配置的电流和电压互感器模拟式容量大。随着电子信息技术的高速发展和在电力系统中的扩大化应用,继电保护装置也相应普及于电力系统中,同时采用计算机控制。这些微机控制的数字式设备功能强大、反应速度快、测量精度高、电压和电流的回路能耗小。电流、电压互感器在其供电负荷特性发生变化的过程中,其二次参数并没有发生相应的改变,这就导致了参数的不协调。文章对电流、电压互感器参数的选择对测量回路的影响进行了简要分析,以供同行参考。