Supplier selection paradigm: An integrated hierarchical QFD methodology under multiple-criteria environment

A concurrent engineering approach integrating analytic hierarchy process (AHP) with quality function deployment (QFD) in combination with cost factor measure (CFM) has been delineated to rank and subsequently select candidate-suppliers under multiple, conflicting-in-nature criteria environment within a value-chain framework. Engineering requirements and customer requirements governing the selection decision have been identified. The hierarchical QFD methodology allows the decision maker (DM) to rank the candidate-suppliers considering both CFM and the subjective factors. The sensitivity of the proposed methodology is elucidated considering a parameter called objective factor decision weight. The devised methodology has been tested with the dataset adopted from Yahya and Kingsman [89]. Liu and Hai [51] tested their model with the same dataset. A comparative analysis using design of experiment has been elucidated so as to demonstrate the efficacy of the devised hierarchical concurrent engineering approach.     

Supplier selection using AHP methodology extended by D numbers

Supplier selection is an important issue in supply chain management (SCM), and essentially is a multi-criteria decision-making problem. Supplier selection highly depends on experts’ assessments. In the process of that, it inevitably involves various types of uncertainty such as imprecision, fuzziness and incompleteness due to the inability of human being’s subjective judgment. However, the existing methods cannot adequately handle these types of uncertainties. In this paper, based on a new effective and feasible representation of uncertain information, called D numbers, a D-AHP method is proposed for the supplier selection problem, which extends the classical analytic hierarchy process (AHP) method. Within the proposed method, D numbers extended fuzzy preference relation has been involved to represent the decision matrix of pairwise comparisons given by experts. An illustrative example is presented to demonstrate the effectiveness of the proposed method.     

Optimum adaptive control in an unknown environment

This correspondence describes the formulation and solution of a nonlinear, non-Gaussian stochastic control problem. Dynamic programming is used to obtain the solution to the problem of optimally controlling a robot, equipped with sensors, that is operating in an unknown environment.     

An integrated supplier selection methodology incorporating QFD and DEA with imprecise data

Supplier evaluation and selection is an important group decision making problem that involves not only quantitative criteria but also qualitative factors incorporating vagueness and imprecision. This paper proposes a novel fuzzy multi-criteria group decision making framework for supplier selection integrating quality function deployment (QFD) and data envelopment analysis (DEA). The proposed methodology allows for considering the impacts of inner dependence among supplier assessment criteria through constructing a house of quality (HOQ). The lower and upper bounds of the weights of supplier assessment criteria are identified by adopting fuzzy weighted average (FWA) method that enables the fusion of imprecise and subjective information expressed as linguistic variables. An imprecise DEA methodology is implemented for supplier selection, which employs the weights of supplier assessment criteria computed by FWA utilizing the data from the HOQ and the supplier ratings with respect to supplier assessment criteria. The application of the proposed framework is demonstrated through a case study in a private hospital in Istanbul.     

开放环境下未知材质的识别技术

针对开放环境下未知物体材质识别的问题,本文提出一种利用欧氏距离区分未知类别和已知类别的物体材质识别方法框架,在该框架下利用支持向量机对物体材质进行识别,分类效果显著。该方法利用距离度量中的欧氏距离与阈值进行比较,距离的均值小于阈值的物体判定为已知类别物体材质,并进行分类;距离大于阈值的物体判定为未知类别物体材质,并利用支持向量机算法进行重新学习识别。本文在慕尼黑工业大学的触觉数据集中的声音数据上进行实验,对比了5种距离度量方法,选择了欧氏距离;与开集稀疏表示分类方法对比,显示出本文提出的方法在声音数据集上具有一定的优势;通过实验选出了合理的阈值,并最终实现了开放环境下识别所有物体材质。实验验证了该框架可以很好地解决开放环境下触觉感知信息的物体材质识别问题。     

Multi-robot exploration and terrain coverage in an unknown environment

Terrain exploration and coverage are required for a variety of applications such as mine clearing, intrusion detection and other humanitarian missions like search and rescue operations, for example, fire or blast in a building. During an emergency situation within a building it is crucial to explore the area as fast as possible in order to search and find the wounded people and other hazards. On account of the prevailing breakdown of communication in indoor environments in some situations, it is suggested that the robots can communicate indirectly with the use of markings in the environment. The Spanning Tree Coverage (STC) method, proposed for this problem, suffers in environments that have partially occupied cells and narrow door openings between rooms. In this paper, we consider an extension of the Simultaneous Multiple STC (S-MSTC) algorithm, which we proposed in our previous work on multiple autonomous robots used in exploration and coverage in an unknown terrain. The proposed extended S-MSTC (ES-MSTC) uses ant-type robots to cover the terrain leaving marks on the terrain, which can be sensed by the robots and allow them to cover the terrain, similar to the nature of ants. This algorithm can handle partially occupied cells and narrow door openings in the terrain and performs a complete coverage of the surface regardless of the shape of the environment by constructing multiple spanning trees simultaneously. We present a simulation study and compare the performance of the ES-MSTC algorithm with other existing algorithms.     

Fault isolation in an integrated diagnostic environment

The use of information flow models to conduct efficient fault isolation strategies is described. Of particular concern is optimizing diagnosis to minimize some objective cost function. A technique that can include multiple cost criteria such as test time, skill level, and failure frequency, as well as information value, is discussed     

Relative debugging in an integrated development environment

Relative Debugging allows a user to compare the internal state of two programs as they run, making it possible to test whether two programs perform the same function given the same input. When implemented with a command line user interface, a relative debugger looks like traditional debugging tools with the addition of commands that describe which structures should be equivalent in the two programs. In this paper, we discuss relative debugging within an integrated development environment, and show that there are significant advantages over a command line form. We describe a pluggable, modular, architecture that works with a variety of different products, including Microsoft's Visual Studio, SUN's NetBeans, and IBM's Eclipse. Copyright © 2009 John Wiley & Sons, Ltd.     

Seeking a path through the crowd: Robot navigation in unknown dynamic environments with moving obstacles based on an integrated environment representation

We present a novel algorithm for collision free navigation of a non-holonomic robot in unknown complex dynamic environments with moving obstacles. Our approach is based on an integrated representation of the information about the environment which does not require to separate obstacles and approximate their shapes by discs or polygons and is very easy to obtain in practice. Moreover, the proposed algorithm does not require any information on the obstacles’ velocities. Under our navigation algorithm, the robot efficiently seeks a short path through the crowd of moving or steady obstacles. A mathematically rigorous analysis of the proposed approach is provided. The performance of the algorithm is demonstrated via experiments with a real robot and extensive computer simulations.     

Constructing an integrated visual programming environment

This paper presents an object-oriented architecture, called the Model-View-Shape (MVS) architecture, for constructing an Integrated Visual Programming Environment (IVPE), whose constituent tools deal with (fine-grained) language semantics, as well as a mass of graphics-drawing activities. This architecture enforces a layered and loosely-coupled structure, so that the user-interface part of components may be more independent, maintainable, and reusable than those proposed in the original model-view-controller architecture. An MVS class hierarchy, systematically constructed using C++, can be reused and extended with new semantics to rapidly develop new tools for an existing IVPE, or even an IVPE supporting more than one language. The present editors developed can be used to construct programs by specifying the associated flow information in explicit (visual) or implicit (textual) ways, while the (incremental) flow analysers can help analyse incomplete program fragments to locate and inform the user of possible errors or anomalies during programming. © 1998 John Wiley & Sons, Ltd.     

Planning smooth paths for mobile robots in an unknown environment

This paper addresses the path planning problem for autonomous mobile robots operating in an unknown environment with obstacles. Paths are formed based on third-order Bezier splines and, then, are corrected on the move as a robot detects obstacles with its onboard sensors. During this correction, the initial path between two reference points is divided into two segments (described by Bezier splines) in such a way as to allow the robot to move at a safe distance from a detected obstacle along a smooth resultant trajectory. In this case, the use of smooth paths ensures a high levels of accuracy and velocity of mobile robots during their operation.     

Supplier selection in the airline retail industry using a funnel methodology: Conjunctive screening method and fuzzy AHP

Since a company can only perform as well as it is allowed to by its suppliers, the importance of supplier selection in supply chain management has been increasingly recognized. Supplier selection can best be described as a highly complex process, due to the involvement of many, sometimes conflicting, qualitative and quantitative criteria. The objective is to select the most suitable supplier(s) that meet a company’s specific needs. This paper investigates supplier selection in the airline retail industry. We discuss a number of issues that make airline retail complex and distinguish it from conventional retail. The supplier selection problem is solved by means of a two-phased methodology. In the first phase, a conjunctive screening method is used, which aims to reduce the initial set of potential suppliers prior to the comprehensive final choice phase. In the second phase, a fuzzy analytic hierarchy process (AHP) is used, in which suppliers are evaluated against the main criteria and sub-criteria. By combining the decision-maker’s preferences, using the developed methodology will eventually result in a ranking of suppliers that makes it possible to select the most suitable supplier(s). The proposed methodology is applied to one of the largest airlines in Europe, the Royal Dutch Airlines (KLM), and the results are discussed extensively in this paper. We conclude by proposing avenues for future research regarding the general applicability and further extensions.     

Supplier selection model with contingency planning for supplier failures

We consider the optimal allocation of demand across a set of suppliers given the risk of supplier failures. We assume items sourced are used in multiple facilities and can be purchased from multiple suppliers with different cost and reliability characteristics. Suppliers have production flexibility that allows them to deliver a contingency quantity in case other suppliers fail. Costs considered include supplier fixed costs and variable costs per unit, while failure to deliver to a demand point results in a particular financial loss. The model utilizes the decision tree approach to consider all the possible states of nature when one or more suppliers fail, as well as expand the traditional transportation problem. Unlike other supplier selection models, this model considers contingency planning in the decision process, minimizing the total network costs. This results in a base allocation to one or more of the available suppliers and a state of nature specific delivery contingency plan from the suppliers to each demand point. A numerical example, as well as sensitivity analysis, is presented to illustrate the model and provide insights.     

Concepts of an integrated project support environment

The need for an integrated approach to system development and maintenance has been apparent for sometime, and has been discussed in a series of conferences on software engineering. Although the phrase Integrated Project Support Environment (IPSE) is new, the concept is not. A UK company is developing such an environment, to be available commercially in early 1986.     

室外未知环境下的AGV地貌主动探索感知

智能机器人对复杂地貌环境的识别一直是机器人应用领域研究的前沿问题,移动机器人在不同的地貌上采取的运动方式并非一成不变,所以选择的运动方式对于迅速准确识别所处地貌的类型至关重要。针对该问题本文提出了一种基于贝叶斯框架的主动感知探索方法,使移动机器人能够主动探索有兴趣的运动方式并且感知识别和运动之间的匹配关系,可以优化在地貌识别之中的模糊不确定性;为了进一步验证实验的可靠性,还使用了被动感知策略来比较和分析不同策略之间的差异。实验结果表明:主动感知方法能够规划出有效的地貌识别动作序列,能够引导移动机器人主动感知目标地貌,该框架对于室外未知环境下主动感知后的地貌识别效果优于被动感知。     

未知环境下群机器人多目标搜索协同控制

未知环境下,群机器人无法预先获取多目标搜索的环境信息,仅可局部感知与局部通信.本文针对避障效率与搜索效率的缺陷提出边界扫描的避障策略和目标位置估计的粒子群算法,边界扫描的避障策略(BSOA)将障碍物简化成连续障碍物与非连续障碍物两种情况,并根据情况向特定边界运动;目标位置估计的粒子群算法(TPEPSO)则利用获取的目标信号估计目标位置,结合粒子群算法到达目标附近,从而实现目标搜索.提出的方法与基于简化虚拟受力分析模型的循障避碰方法(SVF)及扩展粒子群算法(EPSO)、自适应机器人蝙蝠算法(ARBA)仿真比较,搜索效率提高5.72%～21.58%,总能耗减少4.30%～19.11%.     

An integrated logarithmic fuzzy preference programming based methodology for optimum maintenance strategies selection

Selecting optimum maintenance strategies plays a key role in saving cost, and improving the system reliability and availability. Analytic hierarchical process (AHP) is widely used for maintenance strategies selection in the Multiple Criteria Decision-Making (MCDM) field. But the traditional or hybrid AHP methods either produce multiple, even conflict priority results, or have complicated algorithm structures which are unstable to obtain the optimum solution. Therefore, this paper proposes an integrated Logarithmic Fuzzy Preference Programming (LFPP) based methodology in AHP to solve the optimum maintenance strategies selection problem. The multiplicative constraints and deviation variables are applied instead of additive ones to utilize both qualitative and quantitative data, and process the upper and lower triangular fuzzy judgments to obtain the same priorities. The proposed methodology can produce the unique normalized optimal priority vector for fuzzy pairwise comparison matrices, and it is capable of processing all comparison matrices to obtain the global priorities simultaneously and directly in the form of super-matrix according to the different requirements and judgments of decision-makers. Finally, an example is provided to demonstrate the feasibility and validity of the proposed methodology.     

A new integrated methodology using modified Delphi-fuzzy AHP-PROMETHEE for Geospatial Business Intelligence selection

Geospatial Business Intelligence (Geospatial BI) is a system that combines multidimensional analysis and cartographic visualization. It plays an important role in decision making process for enterprises. Adopting such a comprehensive solution may result in the great investment decision for them, so great deal of attention should be given in the selection of the optimal system. As there are many impacting factors in the selection of Geospatial BI system, the same process is considered as a complex multi-criteria decision making problem. In this paper, we explore the application of an integrated methodology for the evaluation of various Geospatial BI alternatives. The proposed methodology integrates the three well-known decision-making techniques, namely Modified Delphi, fuzzy analytic hierarchical process (fuzzy-AHP), and preference ranking organization method for enrichment evaluations (PROMETHEE). In this respect, the modified Delphi is used to select the most impacting factors by a few decision-makers. The fuzzy-AHP is employed to analyze the structure of the problem and to obtain the weights of the qualitative and quantitative criteria, by incorporating the uncertainty values. Then, the PROMETHEE technique is used for optimal ranking of the alternative system choices. A step-by-step, numerical study is illustrated by using the proposed methodology on the decision making problem of a company that is faced to five Geospatial BI solutions. The results demonstrate that the proposed methodology can successfully accomplish our goal of this study.