(R1509) TOPSIS and VIKOR Methods for Spherical Fuzzy Soft Set Aggregating Operator Framework

The Spherical Fuzzy Soft (SFS) set is a generalization of the Pythagorean fuzzy soft set and the intuitionistic fuzzy soft set. We introduce the concept of aggregating SFS decision matrices based on aggregated operations. The techniques for order of preference by similarity to ideal solution (TOPSIS) and viekriterijumsko kompromisno rangiranje (VIKOR) for the SFS approaches are the strong points of multi criteria group decision making (MCGDM), which is various extensions of fuzzy soft sets. We define a score function based on aggregating TOPSIS and VIKOR methods to the SFS-positive and SFS-negative ideal solutions. The TOPSIS and VIKOR methods provide decision-making weights. To find the optimal alternative under this condition, closeness is introduced. Also, we obtain an algorithm that deals with the MCGDM problems based on an aggregating operator. Finally, a numerical example of the MCGDM problem is given to verify the practicality of the aggregating operators

An adjustable approach to multi-criteria group decision-making based on a preference relationship under fuzzy soft information

Group decision-making is a collaborative process to find optimal alternative based on an aggregation judgment. Various techniques have been suggested to solve decision-making problems; however, the rapid growth of uncertainties in industry and organizations highlights the application of fuzzy set theory and soft set theory in this area. In this regard, fuzzy soft model can be considered as an efficient tool in decision-making. To date, different algorithms have been proposed for solving collective decision-making problems based on fuzzy soft set theory. In order to reach the process of consensus, the existing methods have mostly used the t-norms, such as “AND” operator which can be successfully applied to individual decision-making problems including multi-source datasets. However, such approaches fail to consider multi-observer problems in group decision-making processes. Additionally, in the selection step, the existing methods lack a comprehensive priority approach; they focus on a hierarchical preference which ignores incomparable alternatives. To overcome these issues, this paper proposes an adjustable multi-criteria group decision-making approach based on a preference relationship of fuzzy soft sets. First, we construct two topological spaces over the set of objects, and then, develop a preference relationship of objects by using open sets of these two topologies. A multi-phase method is then designed to rank objects in multi-criteria group decision-making problems based on such preference relationship. We also extend the proposed algorithm to weighted case in order to have a higher level of adaptability with real-world problems. Dataset from “www.booking.com” Web site is applied to show the capability of this new method in comparison with results from the well-known literature approaches

A new criterion for soft set based decision making problems under incomplete information

[EN]We put forward a completely redesigned approach to soft set based decision making problems under incomplete information. An algorithmic solution is proposed and compared with previous approaches in the literature. The computational performance of our algorithm is critically analyzed by an experimental study

New Trends in Neutrosophic Theory and Applications Volume II

Neutrosophic set has been derived from a new branch of philosophy, namely Neutrosophy. Neutrosophic set is capable of dealing with uncertainty, indeterminacy and inconsistent information. Neutrosophic set approaches are suitable to modeling problems with uncertainty, indeterminacy and inconsistent information in which human knowledge is necessary, and human evaluation is needed. Neutrosophic set theory was proposed in 1998 by Florentin Smarandache, who also developed the concept of single valued neutrosophic set, oriented towards real world scientific and engineering applications. Since then, the single valued neutrosophic set theory has been extensively studied in books and monographs introducing neutrosophic sets and its applications, by many authors around the world. Also, an international journal - Neutrosophic Sets and Systems started its journey in 2013. Single valued neutrosophic sets have found their way into several hybrid systems, such as neutrosophic soft set, rough neutrosophic set, neutrosophic bipolar set, neutrosophic expert set, rough bipolar neutrosophic set, neutrosophic hesitant fuzzy set, etc. Successful applications of single valued neutrosophic sets have been developed in multiple criteria and multiple attribute decision making. This second volume collects original research and application papers from different perspectives covering different areas of neutrosophic studies, such as decision making, graph theory, image processing, probability theory, topology, and some theoretical papers. This volume contains four sections: DECISION MAKING, NEUTROSOPHIC GRAPH THEORY, IMAGE PROCESSING, ALGEBRA AND OTHER PAPERS. First paper (Pu Ji, Peng-fei Cheng, Hongyu Zhang, Jianqiang Wang. Interval valued neutrosophic Bonferroni mean operators and the application in the selection of renewable energy) aims to construct selection approaches for renewable energy considering the interrelationships among criteria. To do that, Bonferroni mean (BM) and geometric BM (GBM) are employed

Multi-attribute decision-making based on soft set theory: a systematic review

Multi-attribute decision-making (MADM) is a cognitive process for evaluating data under various attributes in order to find the best option in terms of the preferences of decision makers. Handling uncertainty and vagueness in most real-world decision-making problems involves the application of mathematical tools dealing with uncertainty, such as soft set (SS) theory in decision-making processes. In recent years, different approaches have been suggested for demonstrating the effectiveness and efficiency of soft set theory in MADM. To date, no systematic literature review has been presented in this area. However, a review paper on existing SS-based methods can help future researchers to find the gaps and missing MADM approaches in current studies. In this paper, we review the methodologies and applications of 71 research papers published in 30 academic journals (extracted from online databases including ScienceDirect, Scopus, Springer, World of Scientific, and Hindawi) between January 2000 and December 2017. These papers have been categorized into two main groups: single and hybrid approaches. In addition, they have been classified with respect to MADM techniques, country of origin, journal, and publication year. The statistical analysis shows that “SSAW” method which has been employed by various authors is the most common technique. Moreover, the number of research publications by academics was highest in 2017. In addition, the “Applied Mathematical Modelling” journal and China are ranked as the academic journal and country that have presented the most major contributions in this domain, respectively

Parameter reduction analysis under interval-valued m-polar fuzzy soft information

[EN] This paper formalizes a novel model that is able to use both interval representations, parameterizations, partial memberships and multi-polarity. These are differing modalities of uncertain knowledge that are supported by many models in the literature. The new structure that embraces all these features simultaneously is called interval-valued multi-polar fuzzy soft set (IVmFSS, for short). An enhanced combination of interval-valued m-polar fuzzy (IVmF) sets and soft sets produces this model. As such, the theory of IVmFSSs constitutes both an interval-valued multipolar-fuzzy generalization of soft set theory; a multipolar generalization of interval-valued fuzzy soft set theory; and an interval-valued generalization of multi-polar fuzzy set theory. Some fundamental operations for IVmFSSs, including intersection, union, complement, “OR”, “AND”, are explored and investigated through examples. An algorithm is developed to solve decision-making problems having data in interval-valued m-polar fuzzy soft form. It is applied to two numerical examples. In addition, three parameter reduction approaches and their algorithmic formulation are proposed for IVmFSSs. They are respectively called parameter reduction based on optimal choice, rank based parameter reduction, and normal parameter reduction. Moreover, these outcomes are compared with existing interval-valued fuzzy methods; relatedly, a comparative analysis among reduction approaches is investigated. Two real case studies for the selection of best site for an airport construction and best rotavator are studied.J. C. R. Alcantud is grateful to the Junta de Castilla y León and the European Regional Development Fund (Grant CLU-2019-03) for the financial support to the research unit of excellence “Economics Management for Sustainability” (GECOS).Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCL

An analysis of consensus approaches based on different concepts of coincidence

The file attached to this record is the author's final peer reviewed version.Soft consensus is a relevant topic in group decision making problems. Soft consensus measures are utilized to reflect the different agreement degrees between the experts leading the consensus reaching process. This may determine the final decision and the time needed to reach it. The concept of coincidence has led to two main approaches to calculating the soft consensus measures, namely, concordance among expert preferences and concordance among individual solutions. In the first approach the coincidence is obtained by evaluating the similarity among the expert preferences, while in the second one the concordance is derived from the measurement of the similarity among the solutions proposed by these experts. This paper performs a comparative study of consensus approaches based on both coincidence approaches. We obtain significant differences between both approaches by comparing several distance functions for measuring expert preferences and a consensus measure over the set of alternatives for measuring the solutions provided by experts. To do so, we use the nonparametric Wilcoxon signed-ranks test. Finally, these outcomes are analyzed using Friedman mean ranks in order to obtain a quantitative classification of the considered measurements according to the convergence criterion considered in the consensus reaching process

Intertemporal Choice of Fuzzy Soft Sets

This paper first merges two noteworthy aspects of choice. On the one hand, soft sets and fuzzy soft sets are popular models that have been largely applied to decision making problems, such as real estate valuation, medical diagnosis (glaucoma, prostate cancer, etc.), data mining, or international trade. They provide crisp or fuzzy parameterized descriptions of the universe of alternatives. On the other hand, in many decisions, costs and benefits occur at different points in time. This brings about intertemporal choices, which may involve an indefinitely large number of periods. However, the literature does not provide a model, let alone a solution, to the intertemporal problem when the alternatives are described by (fuzzy) parameterizations. In this paper, we propose a novel soft set inspired model that applies to the intertemporal framework, hence it fills an important gap in the development of fuzzy soft set theory. An algorithm allows the selection of the optimal option in intertemporal choice problems with an infinite time horizon. We illustrate its application with a numerical example involving alternative portfolios of projects that a public administration may undertake. This allows us to establish a pioneering intertemporal model of choice in the framework of extended fuzzy set theorie

A holistic multi-methodology for sustainable renovation

A review of the barriers for building renovation has revealed a lack of methodologies, which can promote sustainability objectives and assist various stakeholders during the design stage of building renovation/retrofitting projects. The purpose of this paper is to develop a Holistic Multi-methodology for Sustainable Renovation, which aims to deal with complexity of renovation projects. It provides a framework through which to involve the different stakeholders in the design process to improve group learning and group decision-making, and hence make the building renovation design process more robust and efficient. Therefore, the paper discusses the essence of multifaceted barriers in building renovation regarding cultural changes and technological/physical changes. The outcome is a proposal for a multi-methodology framework, which is developed by introducing, evaluating and mixing methods from Soft Systems Methodologies (SSM) with Multiple Criteria Decision Making (MCDM). The potential of applying the proposed methodology in renovation projects is demonstrated through a case study

Fuzzy investment decision support for brownfield redevelopment

Tato disertační práce se zaměřuje na problematiku investování a podporu rozhodování pomocí moderních metod. Zejména pokud jde o analýzu, hodnocení a výběr tzv. brownfieldů pro jejich redevelopment (revitalizaci). Cílem této práce je navrhnout univerzální metodu, která usnadní rozhodovací proces. Proces rozhodování je v praxi komplikován též velkým počet relevantních parametrů ovlivňujících konečné rozhodnutí. Navržená metoda je založena na využití fuzzy logiky, modelování, statistické analýzy, shlukové analýzy, teorie grafů a na sofistikovaných metodách sběru a zpracování informací. Nová metoda umožňuje zefektivnit proces analýzy a porovnávání alternativních investic a přesněji zpracovat velký objem informací. Ve výsledku tak bude zmenšen počet prvků množiny nejvhodnějších alternativních investic na základě hierarchie parametrů stanovených investorem.This dissertation focuses on decision making, investing and brownfield redevelopment. Especially on the analysis, evaluation and selection of previously used real estates suitable for commercial use. The objective of this dissertation is to design a method that facilitates the decision making process with many possible alternatives and large number of relevant parameters influencing the decision. The proposed method is based on the use of fuzzy logic, modeling, statistic analysis, cluster analysis, graph theory and sophisticated methods of information collection and processing. New method allows decision makers to process much larger amount of information and evaluate possible investment alternatives efficiently.