Fatih Emre Boran

A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method

Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain. On the other hand, it is a hard problem since supplier selection is typically a multi criteria group decision-making problem involving several conflicting criteria on which decision makers knowledge is usually vague and imprecise. In this study, TOPSIS method combined with intuitionistic fuzzy set is proposed to select appropriate supplier in group decision making environment. Intuitionistic fuzzy weighted averaging (IFWA) operator is utilized to aggregate individual opinions of decision makers for rating the importance of criteria and alternatives. Finally, a numerical example for supplier selection is given to illustrate application of intuitionistic fuzzy TOPSIS method.

Interval multiplicative transitivity for consistency, missing values and priority weights of interval fuzzy preference relations

In this paper, the concept of multiplicative transitivity of a fuzzy preference relation, as defined by Tanino T. Tanino, Fuzzy preference orderings in group decision-making, Fuzzy Sets and Systems 12 (1984) 117-131, is extended to discover whether an interval fuzzy preference relation is consistent or not, and to derive the priority vector of a consistent interval fuzzy preference relation. We achieve this by introducing the concept of interval multiplicative transitivity of an interval fuzzy preference relation and show that, by solving numerical examples, the test of consistency and the weights derived by the simple formulas based on the interval multiplicative transitivity produce the same results as those of linear programming models proposed by Xu and Chen Z.S. Xu, J. Chen, Some models for deriving the priority weights from interval fuzzy preference relations, European Journal of Operational Research 184 (2008) 266-280. In addition, by taking advantage of interval multiplicative transitivity of an interval fuzzy preference relation, we put forward two approaches to estimate missing value(s) of an incomplete interval fuzzy preference relation, and present numerical examples to illustrate these two approaches.

A biparametric similarity measure on intuitionistic fuzzy sets with applications to pattern recognition

Unlike an ordinary fuzzy set, the concept of intuitionistic fuzzy set (IFS), characterized both by a membership degree and by a non-membership degree, is a more flexible way to capture the uncertainty. One of the important topics in IFS is the measure of the similarity between IFSs for which several studies have been proposed in the literature. Some of those, however, cannot satisfy the axioms of similarity, and provide counter-intuitive cases. In this paper, a new general type of similarity measure for IFS with two parameters is proposed along with its proofs. A comparison between the existing similarity measures and the proposed similarity measure is also performed in terms of counter-intuitive cases. The findings indicate that the proposed similarity measure does not provide any counter-intuitive cases.

The Evaluation of Renewable Energy Technologies for Electricity Generation in Turkey Using Intuitionistic Fuzzy TOPSIS

Abstract Due to global warming and climate changes, the utilization of renewable energy not only plays a key role in reducing emissions of greenhouse gases in the world but also will supply global energy in the future. Renewable energy technologies are efficient and effective solutions for clean and sustainable energy development in Turkey due to the advantages of Turkeys geographical location for the extensive usage of most renewable energy resources. In this article, the evaluation of renewable energy technologies for electricity generation in Turkey has been accomplished using intuitionistic fuzzy TOPSIS. Photovoltaic, hydro, wind and geothermal energy have been evaluated for long-term renewable technologies for Turkey.

Optimization of module, shaft diameter and rolling bearing for spur gear through genetic algorithm

In this study, the dimensional optimization of motion and force transmitting components of a gearbox is performed by genetic algorithm (GA). It is aimed to obtain the optimal dimensions for gearbox shaft, gear and the optimal rolling bearing. GA is a non-conventional useful search technique. In genetic algorithm, the best results can be obtained within the solution space which is formed by the design constraints. With the optimization of the gearbox components, the design with smallest volume which can carry the system load is obtained. The results obtained by GA optimization are compared to those obtained by analytical methods. These obtained results indicate that GA can be used reliably in machine element design problems.

An overview of methods for linguistic summarization with fuzzy sets

We review the evaluating methods on linguistic summarization.We propose a taxonomy for the methods.We present the differences between methods.We illustrate that fuzzy cardinality based methods provides consistent results. While the rapid development of information technology has made easy to store and access the huge amount of data, it also brings another problem, that of how to extract potentially useful knowledge not only in an efficient way but also in a way that could be easily understandable by humans. One of the solutions to this problem is linguistic summarization, aim of which is to generate explicit and concise summaries from data that is more compatible with human cognitive mechanism. The most crucial step in linguistic summarization is certainly the evaluation of linguistic summaries since they are the most important element of fuzzy rule based systems commonly used in expert systems and intelligent systems. Therefore, the selection of appropriate method for evaluating linguistic summaries in sense of different views such as quality, quantity, relevance and simplicity becomes vital. The aim of this paper is to review the state of art on linguistic summarization in the framework of fuzzy sets, focusing on the methods for evaluating linguistic summaries and the current applications. A taxonomy is proposed to identify the existing methods depending on the type of fuzzy sets (i.e., type-1 fuzzy set and type-2 fuzzy set) and the type of cardinalities (i.e., scalar cardinality and fuzzy cardinality). The recent studies on linguistic summarization are also presented to give a comprehensive framework for the future directions. The paper ends with conclusions, addressing some important issues and open questions which can be subject for future research.

Forecasting Natural Gas Consumption in Turkey Using Grey Prediction

Natural gas, used for heating and electricity generation, has become one of the important energy sources in the world since it provides low level emission of greenhouse gases and has significant economic and other environmental benefits. Turkey, a natural bridge between Europe and the Middle East, is one of the fastest-developing countries in the world. Although Turkey has a small proven natural gas reserve, natural gas consumption has increased in the past few years and it is expected to continue in the future with a chaotic and nonlinear trend. Therefore, the forecasting of natural gas consumption is very important for energy policymakers for future energy planning in Turkey. In this study, a grey prediction with rolling mechanism (GPRM) approach is proposed to predict natural gas consumption and to assist energy policymakers in Turkey. The GPRM approach is utilized since it has high prediction accuracy and applicability when limited data exist. Furthermore, the future projections have been conducted for natural gas consumption in Turkey.

Multi-criteria Axiomatic Design Approach to Evaluate Sites for Grid-connected Photovoltaic Power Plants: A Case Study in Turkey

Abstract Global warming and climate change are the most serious problems for developing countries as well as the world. Therefore, the usage of renewable energy sources is gaining importance for sustainable energy development and environmental protection. Turkey is one of the developing countries whose demand of electricity is sharply increasing. In order to meet this demand by means of renewable sources, solar power is a suitable source due to the high solar energy potential of Turkey among the renewable sources. In this article, the multi-criteria axiomatic design (AD) approach is proposed for the evaluation of sites for a grid-connected photovoltaic power plant (GCPP) in Turkey. For this aim, four evaluation criteria, which have great influence on determination of a GCPP site are taken into account.

A generic method for the evaluation of interval type-2 fuzzy linguistic summaries.

Linguistic summarization has turned out to be an important knowledge discovery technique by providing the most relevant natural language-based sentences in a human consistent manner. While many studies on linguistic summarization have handled ordinary fuzzy sets [type-1 fuzzy set (T1FS)] for modeling words, only few of them have dealt with interval type-2 fuzzy sets (IT2FS) even though IT2FS is better capable of handling uncertainties associated with words. Furthermore, the existent studies work with the scalar cardinality based degree of truth which might lead to inconsistency in the evaluation of interval type-2 fuzzy (IT2F) linguistic summaries. In this paper, to overcome this shortcoming, we propose a novel probabilistic degree of truth for evaluating IT2F linguistic summaries in the forms of type-I and type-II quantified sentences. We also extend the properties that should be fulfilled by any degree of truth on linguistic summarization with T1FS to IT2F environment. We not only prove that our probabilistic degree of truth satisfies the given properties, but also illustrate by examples that it provides more consistent results when compared to the existing degree of truth in the literature. Furthermore, we carry out an application on linguistic summarization of time series data of Europe Brent Spot Price, along with a comparison of the results achieved with our approach and that of the existing degree of truth in the literature.

A Fuzzy Multi Criteria Decision Making to Evaluate Energy Policy Based on an Information Axiom: A Case Study in Turkey

Abstract Turkey has been one of the fastest-growing power markets in the world with its young and growing population, rapid urbanization, strong economic growth and low per-capita electricity consumption for two decades. The recent figures indicate that electric power demand and supply have shown rapid increases over the last few years and is expected to continue in the future. Therefore, selecting the appropriate energy policy is very important for Turkey. In this article, energy policies for Turkey are evaluated using multi criteria axiomatic design including information axiom and fuzzy information axiom due to having subjective and objective criteria in the evaluation of the energy policy problem. Fossil fuels, wind power, nuclear power, natural gas, solar power and hydropower are evaluated in the long term (2008–2018) for Turkey. In the evaluation process, economic, environmental, technical, and social benefits are mainly taken into account as the main criteria.