Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming

This paper proposes a new method to evaluate Decision Making Units (DMUs) under uncertainty using fuzzy Data Envelopment Analysis (DEA). In the proposed multi-objective nonlinear programming methodology both the objective functions and the constraints are considered fuzzy. The coefficients of the decision variables in the objective functions and in the constraints, as well as the DMUs under assessment are assumed to be fuzzy numbers with triangular membership functions. A comparison between the current fuzzy DEA models and the proposed method is illustrated by a numerical example

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

AN EFFICIENT MULTI-CRITERIA DECISION-MAKING APPROACH BASED ON HYBRIDIZING DATA MINING TECHNIQUES AN EFFICIENT MULTI-CRITERIA DECISION-MAKING APPROACH BASED ON HYBRIDIZING DATA MINING TECHNIQUES

Multiple-criteria decision-making (MCDM) that deals with multiple criteria in decision-making environments has been explicitly applied to various decision-making fields. Nevertheless, the critical issues of uncertainty and inaccuracy generally and gradually exists in the majority of the MCDM processes because of (1) prejudice and preference of decision-makers or experts as well as (2) the insufficiency information of the input and output. Therefore, this research efficiently proposed a novel method, FVM-index method, to resolve the limitations happened when MCDM is applied. The FVM-index approach, which consists of the fuzzy set theory (FST), the variable precision rough set (VPRS), and the cluster validity index (CVI) function, not only provides optimized classification results for the datasets but also filters out the uncertainty and inaccuracy instances from surveyed datasets by VPRS theory. Because the datasets are refined by the proposed FVM-index method, the decision makers will be able to effectively obtain the suitable results of MCD

A New Multi-Criteria Decision Making Based on Fuzzy- Topsis Theory

Abstract— In this paper, a new extended method of multi criteria decision making based on fuzzy-Topsis theory is introduced. fuzzy mcdm algorithm for determining the best choice among all possible choices when the data are fuzzy is also presented. Using a new index leads to procedure for choosing fuzzy ideal and negative ideal solutions directly from the fuzzy data observed alternatives.in this algorithm we used triangular fuzzy number. Mostly, it is not possible to gather precise data, so decision making based on these data loses its efficiency. The fuzzy theory has been used to overcome this draw back. In multi-criteria decision making, criteria can correlate with each other, most of which are ignored in classic MCDM. In this paper, correlation coefficient of fuzzy criteria has been studied to adapt the interrelation between criteria and a new algorithm is proposed to obtain decision making. Finally the efficiency of suggested method is demonstrated with an example.

Decision Making Methodology for Heat Sink Material Selection Using a Compromise Ranking and Outranking Method under Fuzzy Environment

This paper proposes judicious selection of heat sink materials by extensive evaluation under consideration of numerous alternative materials and evaluation criteria. This enhances the reliability and life of modern electronic devices. Thermal management of electronic devices relies on stabilizing the component temperature at an acceptable level. A hierarchical decision making framework structure based on novel hybrid fuzzy set theory combined with multi-criteria decision-making (MCDM) model is formed. A fuzzy analytic hierarchical process (FAHP) is more realistic to use linguistic terms to describe the expectation value, perception value and important weight of evaluation criteria. This study comprises six alternatives and seven criteria such as thermal conductivity, density, specific heat, melting point, latent heat of fusion, thermal expansion and cost. The results obtained from FAHP-TOPSIS and FAHP- VIKOR is compared with each other. These results help the designer to choose the apt heat sink material for designing and developing electronic packages

Using data envelopment analysis to defuzzify a group of dependent fuzzy numbers

The defuzzification process converts fuzzy numbers to crisp ones and is an important stage in the implementation of fuzzy systems. In many actual applications, relationships among data indicate their mathematical dependence on one another. Hence, this study proposes a new method based on the Data Envelopment Analysis (DEA) model to defuzzify a group of dependent fuzzy numbers. It also aims to obtain the crisp points that satisfy the characteristics of these data as a group by approximating the optimal solutions within the production possibility set of the DEA model.The proposed method partitions the fuzzy numbers, and the relationships among these numbers are observed as constraints. Finally, the usefulness of this new method is illustrated in a real-world problem

Method to defuzzify groups of fuzzy numbers: Allocation problem application

The desertification process converts fuzzy numbers to crisp ones and is an important stage in the implementation of fuzzy systems.In many actual applications, we encounter cases, in which the observed or derived values of the variables are approximate, yet the variables themselves must satisfy a set of relationships dictated by physical principle.When the observed values do not satisfy the relationships, each value is adjusted until they satisfy the relationships among observed data indicating their mathematical dependence on one another.Hence, this study proposes a new method based on the Data Envelopment Analysis (DEA) model to defuzzify groups of fuzzy numbers.It also aims to assume that each observed value is an approximate number (or a fuzzy number) and the true value (crisp value) is found in the production possibility set of the DEA model.The proposed method partitions the fuzzy numbers and the relationships among these observed data are observed as constraints. The paper presents the model, the computational process and applications in a real problem

REGIONAL AIRCRAFT SELECTION WITH FUZZY PIPRECIA AND FUZZY MARCOS: A CASE STUDY OF THE TURKISH AIRLINE INDUSTRY

Aircraft selection is an important issue in achieving long-term goals in the airline industry. For this issue in which multiple conflicting criteria are involved, the extant literature points to the use of multi-criteria decision-making (MCDM) methods. In this respect, this study aims to propose a systematic and comprehensive framework with a focus on the regional aircraft selection perspective. To achieve this, an integrated fuzzy Pivot Pairwise Relative Criteria Importance Assessment (F-PIPRECIA) and fuzzy Measurement Alternatives and Ranking according to the Compromise Solution (F-MARCOS) approach was employed. In this study, in which six regional aircraft alternatives were evaluated according to 14 criteria, data were collected from five decision experts. As a result, it was found that the most pivotal criterion is C33 (Operational Cost), and the least important criterion is C12 (NOx). In addition, CRJ1000 was identified as the most promising regional aircraft alternative. The results of the application were further validated by applying a three-stage sensitivity analysis. The proposed structure is anticipated to assist airline managers in aircraft selection decisions under uncertainty by offering a robust and systematic tool

Procesos drv: la toma de decisiones como entrenamiento para equipos de trabajo

Este artículo presenta un método orientado a facilitar la toma de decisiones en equipos de trabajo. La propuesta utiliza herramientas de la Teoría de Utilidad Multiatributo, combinadas con Estadística. El artículo contiene una revisión de contribuciones al problema de la decisión con múltiples decisores, y una reflexión sobre características y requerimientos de las prácticas grupales. Además, se describen los fundamentos conceptuales del método. Se  enumeran y explican los pasos necesarios para su aplicación. El método se ejemplifica con la capacitación de un equipo responsable por el desarrollo de un sistema de mantenimiento preventivo. En ésta y otras experiencias, la propuesta resultó motivadora, con buen nivel de logros y amplia colaboración de los participantes. Esta contribución se diferencia de otros aportes, porque visualiza el proceso de toma de decisiones como una interesante posibilidad de capacitación grupal y, por ello, orienta su estrategia a posibilitar el intercambio de conocimientos, afianzar liderazgos, aumentar la cohesión interna y favorecer el compromiso con la decisión adoptada.This paper presents a method designed to facilitate group decision making. The proposal relies on tools of the Multiattribute Utility Theory combined with Statistics. The article contains a review of contributions to the problem of multiple decision makers and a reflection on the characteristics and requirements of group practices. It describes the conceptual foundations of the method and it also identifies and explains the steps needed for implementation. The method is exemplified with the training of a team responsible for the development of a preventive maintenance system. In this and other experiences, the proposal was motivating, with good level of achievements and ex-tensive collaboration of the participants. This contribution differs from others because it considers the decision making process as an interesting possibility for group training and therefore gears its strategy to enable knowledge exchange, strengthen leadership, improve internal cohesion and foster commitment to the adopted decision