Shiv Prasad Yadav

Bio: Shiv Prasad Yadav is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Fuzzy logic & Fuzzy number. The author has an hindex of 20, co-authored 82 publications receiving 1300 citations. Previous affiliations of Shiv Prasad Yadav include Indian Institutes of Technology.

A multicriteria intuitionistic fuzzy group decision making for plant location selection with ELECTRE method

Abstract: Plant location selection, the process of finding a suitable location for plant of a project has a strong influence on the success of industrial venture with the goal to minimize cost and maximize the use of resources. Thus, plant location selection problem is a multicriteria decision-making problem involving several conflicting criteria on which decision makers' knowledge is vague and imprecise. Therefore, in this study, the elimination and choice translating reality (ELECTRE) method is proposed with intuitionistic fuzzy sets for selection of appropriate plant location in group decision-making environment to tackle uncertainty of the information provided by decision makers and a plant location selection problem is considered to illustrate the proposed intuitionistic fuzzy-ELECTRE method. The ratings of alternatives with respect to each criterion and the weights of each criterion are taken as linguistic terms further characterized by triangular intuitionistic fuzzy sets.

A fuzzy DEA model with undesirable fuzzy outputs and its application to the banking sector in India

Abstract: Data envelopment analysis (DEA) is a widely used technique for measuring the relative efficiencies of decision making units (DMUs) with multiple inputs and multiple outputs. However, in real life applications, undesirable outputs may be present in the production process which needs to be minimized. The present study endeavors to propose a DEA model with undesirable outputs and further to extend it in fuzzy environment in view of the fact that input/output data are not always available in exact form in real life problems. We propose a fuzzy DEA model with undesirable fuzzy outputs which can be solved as crisp linear program for each α in (0, 1] using α -cut approach. Further, cross-efficiency technique is applied to increase the discrimination power of the proposed models and to rank the efficient DMUs at every α in (0, 1]. Moreover, for better understanding of the proposed methodology, we present a numerical illustration followed by an application to the banking sector in India. This is the first study which attempts to measure the performance of public sector banks (PuSBs) in India using fuzzy input/output data for the period 2009–2011. The results obtained from the proposed methodology not only depict the impact of undesirable output on the performance of PuSBs but also analyze efficiently the influence of the presence of uncertainty in the data over the efficiency results. The findings show that the efficiency results of many PuSBs vary with the variation in α during the selected period.

A new approach for solving intuitionistic fuzzy transportation problem of type-2

Abstract: In solving real life transportation problem, we often face the state of uncertainty as well as hesitation due to various uncontrollable factors. To deal with uncertainty and hesitation many authors have suggested the intuitionistic fuzzy representation for the data. In this paper, we formulate a transportation problem in which costs are triangular intuitionistic fuzzy numbers. We have defined accuracy function using score functions for membership and non membership functions of triangular intuitionistic fuzzy numbers. Then ordering of triangular intuitionistic fuzzy numbers using accuracy function has been proposed. We have utilized this ordering to develop methods for finding starting basic feasible solution in terms of triangular intuitionistic fuzzy numbers. Also the same ordering is utilized to develop intuitionistic fuzzy modified distribution method for finding the optimal solution. Finally the method is illustrated by a numerical example which is followed by graphical representation and discussion of the finding.

A concept of fuzzy input mix-efficiency in fuzzy DEA and its application in banking sector

Abstract: Data envelopment analysis (DEA) is a linear programming based non-parametric technique for evaluating the relative efficiency of homogeneous decision making units (DMUs) on the basis of multiple inputs and multiple outputs. There exist radial and non-radial models in DEA. Radial models only deal with proportional changes of inputs/outputs and neglect the input/output slacks. On the other hand, non-radial models directly deal with the input/output slacks. The slack-based measure (SBM) model is a non-radial model in which the SBM efficiency can be decomposed into radial, scale and mix-efficiency. The mix-efficiency is a measure to estimate how well the set of inputs are used (or outputs are produced) together. The conventional mix-efficiency measure requires crisp data which may not always be available in real world applications. In real world problems, data may be imprecise or fuzzy. In this paper, we propose (i) a concept of fuzzy input mix-efficiency and evaluate the fuzzy input mix-efficiency using @a - cut approach, (ii) a fuzzy correlation coefficient method using expected value approach which calculates the expected intervals and expected values of fuzzy correlation coefficients between fuzzy inputs and fuzzy outputs, and (iii) a new method for ranking the DMUs on the basis of fuzzy input mix-efficiency. The proposed approaches are then applied to the State Bank of Patiala in the Punjab state of India with districts as the DMUs.

Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014

Abstract: Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

Fuzzy Multicriteria Decision-Making: A Literature Review

Abstract: 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.