Generalized Hamacher aggregation operators for intuitionistic uncertain linguistic sets: Multiple attribute group decision making methods

© 2019 by the authors. In this paper, we consider multiple attribute group decision making (MAGDM) problems in which the attribute values take the form of intuitionistic uncertain linguistic variables. Based on Hamacher operations, we developed several Hamacher aggregation operators, which generalize the arithmetic aggregation operators and geometric aggregation operators, and extend the algebraic aggregation operators and Einstein aggregation operators. A number of special cases for the two operators with respect to the parameters are discussed in detail. Also, we developed an intuitionistic uncertain linguistic generalized Hamacher hybrid weighted average operator to reflect the importance degrees of both the given intuitionistic uncertain linguistic variables and their ordered positions. Based on the generalized Hamacher aggregation operator, we propose a method for MAGDM for intuitionistic uncertain linguistic sets. Finally, a numerical example and comparative analysis with related decision making methods are provided to illustrate the practicality and feasibility of the proposed method

Fuzzy Logic in Decision Support: Methods, Applications and Future Trends

During the last decades, the art and science of fuzzy logic have witnessed significant developments and have found applications in many active areas, such as pattern recognition, classification, control systems, etc. A lot of research has demonstrated the ability of fuzzy logic in dealing with vague and uncertain linguistic information. For the purpose of representing human perception, fuzzy logic has been employed as an effective tool in intelligent decision making. Due to the emergence of various studies on fuzzy logic-based decision-making methods, it is necessary to make a comprehensive overview of published papers in this field and their applications. This paper covers a wide range of both theoretical and practical applications of fuzzy logic in decision making. It has been grouped into five parts: to explain the role of fuzzy logic in decision making, we first present some basic ideas underlying different types of fuzzy logic and the structure of the fuzzy logic system. Then, we make a review of evaluation methods, prediction methods, decision support algorithms, group decision-making methods based on fuzzy logic. Applications of these methods are further reviewed. Finally, some challenges and future trends are given from different perspectives. This paper illustrates that the combination of fuzzy logic and decision making method has an extensive research prospect. It can help researchers to identify the frontiers of fuzzy logic in the field of decision making

Pythagorean fuzzy combinative distance-based assessment with pure linguistic information and its application to financial strategies of multi-national companies

This article addresses the issue of selecting Financial Strategies in Multi-National companies (F.S.M.). The F.S.M. typically has to consider multiple factors involving multiple stakeholders and, hence, can be handled by applying an appropriate Multi-Criteria Group Decision-Making (M.C.G.D.M.) approach. To address this issue, we develop an M.C.G.D.M. framework to tackle the F.S.M. problem. To handle inherent uncertainty in business decisions as reflected by linguistic reasoning, we embark on constructing a Linguistic Pythagorean Fuzzy (L.P.F.) M.C.G.D.M. framework that is capable of tackling both uncertain decision information and linguistic variables. The proposed approach extends the combinative distancebased assessment (C.O.D.A.S.) method into the L.P.F. environment, and processes decision input expressed as Pythagorean fuzzy sets (P.F.S.) and pure linguistic variables (rather than converting linguistic information into fuzzy numbers). The developed L.P.F.- C.O.D.A.S. technique aggregates the L.P.F. information and is applied to the F.S.M. problem with uncertain linguistic information. A comparative analysis is carried out to compare the results obtained from the proposed L.P.F.-C.O.D.A.S. approach with those from other extensions of C.O.D.A.S. Furthermore, a sensitivity analysis is conducted to check the impact of changes in a distance threshold parameter on the ranking results

Investment decision analysis of international megaprojects based on cognitive linguistic cloud models

The investment decision analysis of international megaprojects is a major area of interest. The choice of interna tional megaprojects usually depends on the multi-discipline knowledge from experts. Besides, experts may not be able to provide accurate or crisp evaluations such as deterministic numbers on each criterion because of the complexity of the decision problem. In this case, natural evaluation language, either single linguistic variable or multiple linguistic variables, is a good expression tool for experts to sharing their opinions freely and flexibly. To this end, this paper introduces a cognitive linguistic cloud model for the investment decision analysis of international megaprojects as a decision support system and provides a survey of the cloud model. Afterwards, the technique to tackle multi-granularity of cognitive linguistic information is proposed to capture personalized semantics. In addition, operators of the cognitive linguistic model are proposed to aggregate natural language. The proposed approach has the advantages of more accurate utilization of experts’ knowledge, reducing uncertainties, and more effective operations of cognitive clouds for decision analysis in comparing with the state of the art. Finally, a case study about the investment of international megaprojects is given to show the flexibility and understandability of the cognitive linguistic model

Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets

Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (, , ), where is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, is the opposite of , while is the neutral (or indeterminate) between them, i.e., neither nor .Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures – that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc

A new outranking method for multicriteria decision making with complex Pythagorean fuzzy information

[EN]This article contributes to the advancement and evolution of outranking decision-making methodologies, with a novel essay on the ELimination and Choice Translating REality (ELECTRE) family of methods. Its primary target is to unfold the constituents and expound the implementation of the ELECTRE II method for group decision making in complex Pythagorean fuzzy framework. This results in the complex Pythagorean fuzzy ELECTRE II method. By inception, it is intrinsically superior to models using one-dimensional data. It is designed to perform the pairwise comparisons of the alternatives using the core notions of concordance, discordance and indifferent sets, which is then followed by the construction of complex Pythagorean fuzzy concordance and discordance matrices. Further, the strong and weak outranking relations are developed by the comparison of concordance and discordance indices with the concordance and discordance levels. Later, the forward, reverse and average rankings of the alternatives are computed by the dint of strong and weak outranking graphs. This methodology is supported by a case study for the selection of wastewater treatment process, and by a numerical example for the selection of the best cloud solution for a big data project. Its consistency is confirmed by an effectiveness test and comparison analysis with the Pythagorean fuzzy ELECTRE II and complex Pythagorean fuzzy ELECTRE I methodsPublicación 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

Fuzzy Analytic Hierarchy Process Utilization in Government Projects : A Systematic Review of Implementation Processes

Uncertain assessments challenge the aggregation of expert knowledge in the field of decision-making. Valuable, yet sometimes hesitant, insight of expert decision makers needs to be converted into numerically comparative form in the age of information management. . Fuzzy Analytic Hierarchy Process (FAHP) enables the comparison of decision elements through expert judgements, even when the information at hand is uncertain. The present study explores Fuzzy Analytic Hierarchy Process (FAHP) implementation in government projects in a systematic literature review. Theoretical framework for Analytic Hierarchy Process (AHP), Fuzzy Set Theory (FST) and their combination, namely Fuzzy Analytic Hierarchy Process (FAHP) is provided. The systematic literature review categorizes research results under three categories and examines each paper by utilizing review questions. Three main application purposes rise from the literature review; policy planning and assessment, project selection and project and performance evaluation. Overall implementation processes of the three application areas are discussed. The conclusion provides comprehensive evaluation of the approach and considerations for practitioners.Asiantuntijanäkemysten epävarmuus vaikeuttaa tiedon keräämistä päätöksenteossa. Päätöksentekoprosessin kannalta arvokkaat, vaikkakin joskus epävarmat, asiantuntijanäkemykset tulee voida muuttaa numerollisesti vertailtavaan muotoon tietojohtamisen aikakautena. Sumea Analyyttinen Hierarkiaprosessi mahdollistaa päätöksenteossa käytettävien elementtien vertailun asiantuntija-arviointien avulla, jopa silloin kun käytettävissä oleva tieto on epävarmaa. Opinnäytetyössä tutkitaan systemaattisen kirjallisuuskatsauksen keinoin Sumean Analyyttisen Hierarkiaprosessin, eng. Fuzzy Analytic Hierarchy Process (FAHP), implementointia julkishallinnon hankkeissa. Tutkimus sisältää teoreettisen viitekehyksen Analyyttisen Hierarkiaprosessin, Sumean joukko-opin, eng. Fuzzy Set Theory (FST) ja niiden yhdistelmän, Sumean Analyyttisen Hierarkiaprosessin, eng. Fuzzy Analytic Hierarchy Process (FAHP), ymmärtämisen tueksi. Systemaattisen kirjallisuuskatsauksen myötä valittu aineisto luokitellaan kolmeen kategoriaan ja jokaista tutkimusta tarkastellaan ennalta määrättyjen kysymysten avulla. Systemaattisen kirjallisuuskatsaukseen myötä valittujen tutkimusten kolme olennaisinta käyttötarkoitusta ovat; käytännön suunnittelu ja arviointi, hankevalinta sekä hankkeiden ja suoritusten arviointi. Aineiston luokittelun jälkeen tutkimus etenee tarkastelemaan erilaisiin käyttötarkoituksiin suunnattujen Sumean Analyyttisen Hierarkiaprosessi -metodin implementointiprosesseja. Johtopäätös -osio tarjoaa pohdintaa ja huomioita siitä, miten päätöksentekijät voivat suhtautua Sumean Analyyttisen Hierarkiaprosessin hyödyntämiseen julkishankkeiden yhteydessä

The Risky-Opportunity Analysis Method (ROAM) to Support Risk-Based Decisions in a Case-Study of Critical Infrastructure Digitization

none4Ali Aghazadeh Ardebili; Elio Padoano; Antonella Longo; Antonio FicarellaAGHAZADEH ARDEBILI, Ali; Padoano, Elio; Longo, Antonella; Ficarella, Antoni

CLOUD SERVICE REVENUE MANAGEMENT

Successful Internet service offerings can only thrive if customers are satisfied with service performance. While large service providers can usually cope with fluctuations of customer visits retaining acceptable Quality of Service, small and medium-sizes enterprises face a big challenge due to limited resources in the IT infrastructure. Popular services, such as justin.tv and SmugMug, rely on external resources provided by cloud computing providers in order to satisfy their customers demands at all times. The paradigm of cloud computing refers to the delivery model of computing services as a utility in a pay-as-you-go manner. In this paper, we provide and computationally evaluate decision models and policies that can help cloud computing providers increase their revenue under the realistic assumption of scarce resources and under both informational certainty and uncertainty of customers? resource requirement predictions. Our results show that in both cases under certainty and under uncertainty applying the dynamic pricing policy significantly increases revenue while using the client classification policy substantially reduces revenue. We also show that, for all policies, the presence of uncertainty causes losses in revenue; when the client classification policy is applied, losses can even amount to more than 8%