Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Type-2 neutrosophic number based multi-attributive border approximation area comparison (MABAC) approach for offshore wind farm site selection in USA.

The technical, logistical, and ecological challenges associated with offshore wind development necessitate an extensive site selection analysis. Technical parameters such as wind resource, logistical concerns such as distance to shore, and ecological considerations such as fisheries all must be evaluated and weighted, in many cases with incomplete or uncertain data. Making such a critical decision with severe potential economic and ecologic consequences requires a strong decision-making approach to ultimately guide the site selection process. This paper proposes a type-2 neutrosophic number (T2NN) fuzzy based multi-criteria decision-making (MCDM) model for offshore wind farm (OWF) site selection. This approach combines the advantages of neutrosophic numbers sets, which can utilize uncertain and incomplete information, with a multi-attributive border approximation area comparison that provides formulation flexibility and easy calculation. Further, this study develops and integrates a techno-economic model for OWFs in the decision-making. A case study is performed to evaluate and rank five proposed OWF sites off the coast of New Jersey. To validate the proposed model, a comparison against three alternative T2NN fuzzy based models is performed. It is demonstrated that the implemented model yields the same ranking order as the alternative approaches. Sensitivity analysis reveals that changing criteria weightings does not affect the ranking order

Gestão de Recursos Finitos em Empresas

The present work has as goal aiding decision makers, researchers, enterprises and practitioners by developing a proper literature review as a base for comparison among multiple-criteria decision making methods in finite resources management according to each of the most important areas of a business environment. Efficient resource management decision making in companies impacts its value creation capability and, therefore, its competitiveness and ultimate success. The methodology for paper research follows the PRISMA flow diagram, for correct paper filtrations according to the set of criteria stablished in alignment with the thesis goal. The papers included in the study are any that employ multiple-criteria decision making methods in their pure forms, in combination with each other forming hybrids, or in combination with other mathematical techniques for solving decision making problems across five major areas of a company’s body. The five major areas are: (1) Supply Chain Management and Logistics; (2) Environmental Management; (3) Business and Marketing Management; (4) Design, Engineering and Manufacturing Systems; and (5) Human Resources Management. The 204 final papers are presented separated by their corresponding application areas, ordered by number of citations, which is used as a measure of their scientific community relevance. They are also classified by, author, nationality, journal, year, type of research and methods used. All collected data is used for quantitative statistical analysis, with which is possible to collect more in-depth information on the literature research. Focused comments on the main methods are also present in this work, with observations made on the many applications and variations each of them had throughout the articles in the research. The AHP and TOPSIS approaches, either with their fuzzy set variations are by far the most popular methods in the referred applications. However, besides them other 51 MCDM or other mathematical techniques are employed in many different combinations and approaches, bringing a very interesting diversity to the study that is very useful for it to be used as a base for comparison among methods. A total number of 111 journals and authors and co-authors of 41 nationalities are involved in the publications between 2012 and 2018, with more than half of papers coming from either India, Turkey or Iran. Many other results are obtained, bringing the readers different perspectives on the subject. This paper contributes to the body of knowledge with a great and insightful overview on MCDM methods application in aiding in challenges part of a business environment, so that companies can better manage their resources and be more prosperous. It is a vast database that allows many comparisons and evaluations, offering more analysis than the standard literature review articles.O presente trabalho tem como objetivo auxiliar os tomadores de decisão, pesquisadores e profissionais, ao desenvolver uma revisão bibliográfica adequada como base para comparação entre os métodos de decisão multicritério na gestão de recursos finitos de acordo com cada uma das áreas mais importantes de um ambiente de negócios. A tomada eficiente de decisões de gestão de recursos nas empresas afeta sua capacidade de criação de valor e, portanto, sua competitividade e sucesso finais. A metodologia da investigação baseou-se na metodologia PRISMA, para a correta filtração das publicações de acordo com o conjunto de critérios estabelecidos, em alinhamento com o objetivo da tese. Os artigos incluídos no estudo são aqueles que apresentam métodos de decisão com critérios múltiplos em suas formas puras, em combinação uns com os outros ao formar híbridos, ou com outras técnicas matemáticas para resolver problemas em cinco áreas principais das empresas. As cinco áreas são: (1) Gestão da Cadeia de Suprimentos e Logística; (2) Gestão Ambiental; (3) Gestão de Negócios e Marketing; (4) Sistemas de Projeto, Engenharia e Manufatura; e (5) Gestão de Recursos Humanos. Os 204 artigos finais são apresentados de acordo com as áreas de aplicação correspondentes, ordenadas por número de citações, que são usadas como uma medida de sua relevância na comunidade científica. Eles são, ainda, classificados por autor, nacionalidade, revista, ano, tipo de pesquisa e métodos utilizados. Todos os dados coletados são utilizados para análise estatística quantitativa, com a qual é possível recolher informações mais aprofundadas sobre a pesquisa bibliográfica. São realizados comentários sobre os principais métodos e as maneiras que foram apresentados ao longo do estudo de todos os artigos durante a pesquisa. As abordagens AHP e TOPSIS, com suas variações em conjuntos difusos ou fuzzy, são de longe os métodos mais populares nas aplicações referidas. No entanto, além destes, outros 51 MCDM e outras técnicas são utilizadas em muitas combinações e abordagens, trazendo uma diversidade muito interessante para o estudo, servindo de base para comparação dos métodos. Um total de 111 revistas e autores e coautores de 41 nacionalidades estão envolvidos nas publicações entre 2012 e 2018, com mais de metade dos artigos provenientes da Índia, Turquia ou Irão. Estes e outros resultados levam aos leitores diferentes perspectivas sobre o assunto. Este documento contribui para o estado da arte, com um conhecimento geral excelente e perspicaz sobre a aplicação de métodos MCDM para ajudar nos desafios de um ambiente de negócios, para que as empresas possam melhor gerenciar seus recursos e serem mais prósperas. É um vasto banco de dados que permite muitas comparações e avaliações, oferecendo mais análises do que os artigos de revisão de literatura padrão

A hybrid decision support system with golden cut and bipolar q-ROFSs for evaluating the risk-based strategic priorities of fintech lending for clean energy projects

In the last decade, the risk evaluation and the investment decision are among the most prominent issues of efficient project management. Especially, the innovative financial sources could have some specific risk appetite due to the increasing return of investment. Hence, it is important to uncover the risk factors of fintech investments and investigate the possible impacts with an integrated approach to the strategic priorities of fintech lending. Accordingly, this study aims to analyze a unique risk set and the strategic priorities of fintech lending for clean energy projects. The most important contributions to the literature can be listed as to construct an impact-direction map of risk-based strategic priorities for fintech lending in clean energy projects and to measure the possible influences by using a hybrid decision making system with golden cut and bipolar q-rung orthopair fuzzy sets. The extension of multi stepwise weight assessment ratio analysis (M-SWARA) is applied for weighting the risk factors of fintech lending. The extension of elimination and choice translating reality (ELECTRE) is employed for constructing and ranking the risk-based strategic priorities for clean energy projects. In this process, data is obtained with the evaluation of three different decision makers. The main superiority of the proposed model by comparing with the previous models in the literature is that significant improvements are made to the classical SWARA method so that a new technique is created with the name of M-SWARA. Hence, the causality analysis between the criteria can also be performed in this proposed model. The findings demonstrate that security is the most critical risk factor for fintech lending system. Moreover, volume is found as the most critical risk-based strategy for fintech lending. In this context, fintech companies need to take some precautions to effectively manage the security risk. For this purpose, the main risks to information technologies need to be clearly identified. Next, control steps should be put for these risks to be managed properly. Furthermore, it has been determined that the most appropriate strategy to increase the success of the fintech lending system is to increase the number of financiers integrated into the system. Within this framework, the platform should be secure and profitable to persuade financiers.Optimization and upgrading of Industrial structure in Henan Province ; Key Scientific Research Project of Colleges and Universities in Henan Provinc

PROMETHEE-SAPEVO-M1 a Hybrid Approach Based on Ordinal and Cardinal Inputs: Multi-Criteria Evaluation of Helicopters to Support Brazilian Navy Operations

This paper presents a new approach based on Multi-Criteria Decision Analysis (MCDA), named PROMETHEE-SAPEVO-M1, through its implementation and feasibility related to the decision-making process regarding the evaluation of helicopters of attack of the Brazilian Navy. The proposed methodology aims to present an integration of ordinal evaluation into the cardinal procedure from the PROMETHEE method, enabling to perform qualitative and quantitative data and generate the criteria weights by pairwise evaluation, transparently. The modeling provides three models of preference analysis, as partial, complete, and outranking by intervals, along with an intra-criterion analysis by veto threshold, enabling the analysis of the performance of an alternative in a specific criterion. As a demonstration of the application, is carried out a case study by the PROMETHEE-SAPEVO-M1 web platform, addressing a strategic analysis of attack helicopters to be acquired by the Brazilian Navy, from the need to be evaluating multiple specifications with different levels of importance within the context problem. The modeling implementation in the case study is made in detail, first performing the alternatives in each criterion and then presenting the results by three different models of preference analysis, along with the intra-criterion analysis and a rank reversal procedure. Moreover, is realized a comparison analysis to the PROMETHEE method, exploring the main features of the PROMETHEE-SAPEVO-M1. Moreover, a section of discussion is presented, exposing some features and main points of the proposal. Therefore, this paper provides a valuable contribution to academia and society since it represents the application of an MCDA method in the state of the art, contributing to the decision-making resolution of the most diverse real problems.This research was funded by Centre for Research & Development in Mechanical Engineering (CIDEM), School of Engineering of Porto (ISEP), Polytechnic of Porto, Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto, Portugal.info:eu-repo/semantics/publishedVersio

COMPARATIVE ANALYSIS OF SOME PROMINENT MCDM METHODS: A CASE OF RANKING SERBIAN BANKS

In the literature, many multiple criteria decision making methods have been proposed. There are also a number of papers, which are devoted to comparison of their characteristics and performances. However, a definitive answer to questions: which method is most suitable and which method is most effective is still actual. Therefore, in this paper, the use of some prominent multiple criteria decision making methods is considered on the example of ranking Serbian banks. The objective of this paper is not to determine which method is most appropriate for ranking banks. The objective of this paper is to emphasize that the use of various multiple criteria decision making methods sometimes can produce different ranking orders of alternatives, highlighted some reasons which lead to different results, and indicate that different results obtained by different MCDM methods are not just a random event, but rather reality

EDAS method for multiple attribute group decision making with probabilistic dual hesitant fuzzy information and its application to suppliers selection

Probabilistic dual hesitant fuzzy set (PDHFS) is a more powerful and important tool to describe uncertain information regarded as generalization of hesitant fuzzy set (HFS) and dual HFS (DHFS), not only reflects the hesitant attitude of decision-makers (DMs), but also reflects the probability information of DMs. Score function of fuzzy number and weighting method are very important in multi-attribute group decision-making (MAGDM) issues. In many fuzzy environments, the score function and entropy measure have been proposed one after another. Firstly, based on the detailed analysis of the existed score function of PDHF element (PDHFE) and with the help of previous references, we build a novel score function for PDHFE. Secondly, a combined weighting method is built based on the minimum identification information principle by fusing PDHF entropy and Criteria Importance Through Intercriteria Correlation (CRITIC) method. Thirdly, a novel PDHF MAGDM approach (PDHF-EDAS) is built by extending evaluation based on distance from average solution (EDAS) approach to the PDHF environment to solve the issue that the decision attribute information is PDHFE. Finally, the practicability and effectiveness of the PDHF MAGDM technique is verified by suppliers selection (SS) and comparing analysis with existing methods. First published online 23 January 202