Sezi Cevik Onar

Fuzzy Multicriteria Decision-Making: A Literature Review

Multicriteria decision-making (MCDM) refers to making decisions in the presence of multiple and usually conflicting criteria. Fuzzy decision-making is used where vague and incomplete data exist for the solution. Fuzzy multicriteria decision-making is one of the most popular problems handled by the researchers in the literature. In this paper, we survey the latest status of fuzzy multicriteria decision-making methods and classify these methods dividing into two parts: fuzzy multiattribute decision-making (MADM) and fuzzy multiobjective decision-making (MODM). Most of the publications are on fuzzy MADM since there are a plenty of classical multiattribute decision-making methods in the literature. Tabular and graphical illustrations for each method are given.

Multi-criteria evaluation of alternative-fuel vehicles via a hierarchical hesitant fuzzy linguistic model

We concern with a fleet operator considering to adopt an alternative-fuel vehicle.The problem is a multi-expert and multicriteria problem with conflicting criteria.1st major contribution is identification and classification of evaluation criteria.2nd major contribution is a hierarchical hesitant fuzzy linguistic model.The paper presents a real world application with sensitivity and scenario analyzes. Decision on alternative-fuel vehicles is one of the most important problems for fleet operations. In this paper we propose a hierarchical hesitant fuzzy linguistic model that captures hesitant linguistic evaluations of multiple experts on multiple criteria for alternative-fuel vehicles. We apply the proposed model on the alternative-fuel vehicle selection problem of a home health care service provider in the USA. The results show that an electric vehicle is the best fit for the application in todays conditions. We also show robustness of the decision through a sensitivity analysis as well as analyze three scenarios representing possible changes in conditions.

A new hesitant fuzzy QFD approach

Display Omitted A new hesitant fuzzy MCDM method based on linguistic term sets is proposed for QFD.The proposed method is relatively more efficient than the existing QFD approaches.It can aggregate the linguistic assessments of more than one decision maker.The relations between CRs&DRs and correlations among DRs via HFLTS are considered.A sensitivity analysis for robustness check is realized. Computer workstation selection is a multiple criteria decision making problem that is generally based on vague linguistic assessments, which represent human judgments and their hesitancy. In this paper, a new fuzzy quality function deployment (QFD) approach is used to effectively determine the design requirements (DRs) of a computer workstation. Hesitant fuzzy linguistic term sets (HFLTS) are innovatively employed to capture the hesitancy of the experts in this approach. More precisely, the proposed new QFD approach is the first study that determines the importance of customer requirements (CRs), the relations between CRs and DRs and the correlations among DRs via HFLTS. Additionally, HFLTS based Analytic Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) methods are utilized in the computational steps to select the best computer workstation. A real industrial application is carried out to validate the implementation of the proposed approach.

Intuitionistic fuzzy EDAS method: an application to solid waste disposal site selection

AbstractEvaluation based on Distance from Average Solution (EDAS) is a new multicriteria decision making (MCDM) method, which is based on the distances of alternatives from the average scores of attributes. Classical EDAS has been already extended by using ordinary fuzzy sets in case of vague and incomplete data. In this paper, we propose an interval-valued intuitionistic fuzzy EDAS method, which is based on the data belonging to membership, nonmembership, and hesitance degrees. A sensitivity analysis is also given to show how robust decisions are obtained through the proposed intuitionistic fuzzy EDAS. The proposed intuitionistic fuzzy EDAS method is applied to the evaluation of solid waste disposal site selection alternatives. The comparative and sensitivity analyses are also included.

Evaluation of research proposals for grant funding using interval-valued intuitionistic fuzzy sets

It is a well-known fact that the most appealing external funding for a project is grant funding. Therefore, evaluation of research proposal task needs an elaborate approach so as not to finance inconvenient projects. It is indispensable to establish a detailed study for submitted research proposals to have a clearer picture of the grant funding candidates. This study has contributed to research proposal evaluation using a multicriteria approach based on interval-valued intuitionistic fuzzy sets. An interval-valued intuitionistic fuzzy preference relation matrix is initially constructed to determine the relative importance of criteria based on pairwise comparisons in the presence of insufficient information about the criteria. The proposed evaluation method for grand funding allocation problem is composed of six main criteria and 24 sub-criteria. A sensitivity analysis is applied to see the robustness of the decision made.

A Comprehensive Literature Review of 50 Years of Fuzzy Set Theory

AbstractFuzzy sets have a great progress in every scientific research area. It found many application areas in both theoretical and practical studies from engineering area to arts and humanities, from computer science to health sciences, and from life sciences to physical sciences. In this paper, a comprehensive literature review on the fuzzy set theory is realized. In the recent years, ordinary fuzzy sets have been extended to new types and these extensions have been used in many areas such as energy, medicine, material, economics and pharmacology sciences. This literature review also analyzes the chronological development of these extensions. In the last section of the paper, we present our interpretations on the future of fuzzy sets.

Multi-expert Performance Evaluation of Healthcare Institutions Using an Integrated Intuitionistic Fuzzy AHP&DEA Methodology

Abstract Healthcare management and healthcare industry have been one of the popular and complex topics that many researchers and professionals have focused on. This paper proposes a new multi-expert fuzzy approach integrating intuitionistic fuzzy Data Envelopment Analysis (DEA) and intuitionistic fuzzy Analytic Hierarchy Process (IF-AHP) for solving the performance evaluation problem of healthcare institutions. In this paper, intuitionistic fuzzy sets (IFS) have been preferred since they simultaneously provide information on the membership, non-membership, and hesitancy functions. A real life problem is demonstrated to validate the proposed methodology. A total number of 16 hospitals operating in Istanbul have been analyzed based on a broad set of inputs and outputs. Then, a comparison with crisp DEA has been performed.

An analysis of supply chain related graduate programmes in Europe

This is the post-print version of the Article. The official published version of the Article can be accessed from the links below. Copyright @ 2013 Emerald Group Publishing Limited.

Engineering economic analyses using intuitionistic and hesitant fuzzy sets

Engineering economics deals with the investment decisions based on the time value of money. In the real life conditions, the exact estimations of investment parameters are almost impossible. Probabilistic analyses are preferred when sufficient data are available for the estimation of these parameters. Possibilistic analyses should be used when insufficient data exist for the estimation. This paper develops both fuzzy present worth and annual worth analyses using the extensions of fuzzy sets, which are namely intuitionistics fuzzy sets and hesitant fuzzy sets. Each of these extended fuzzy sets is also divided into four subtitles with respect to the types of the data in these economic analyses: Triangular hesitant fuzzy data, triangular intuitionistic fuzzy data, interval-valued hesitant data, and interval-valued intuitionistic fuzzy data. The numerical examples illustrate the applications of the developed analyses.

Risk Analysis of Wind Energy Investments in Turkey

ABSTRACT Wind energy is a reliable source for fulfilling energy demand. However, the wind power usage remains limited due to the investmental risks. Governments’ support on renewable energy compensates these risks partially. Traditional investment evaluation techniques that do not consider the compensations and risks associated with the wind energy investments are one of the main reasons for the limited usage of wind power. In this study a real option and Monte Carlo simulation–based methodology, which considers both risks and compensations associated with these investments, is proposed to evaluate wind energy investments. The model is applied to a wind turbine investment in Turkey in order to show the applicability of the proposed model. The results indicate that the option value created through wind energy investments due to the governmental compensations is very high; therefore the traditional investment techniques are not appropriate for evaluating wind energy investments.