An Extended VIKOR Method for Multiple Criteria Group Decision Making with Triangular Fuzzy Neutrosophic Numbers

In this article, we combine the original VIKOR model with a triangular fuzzy neutrosophic set to propose the triangular fuzzy neutrosophic VIKOR method. In the extended method, we use the triangular fuzzy neutrosophic numbers (TFNNs) to present the criteria values in multiple criteria group decision making (MCGDM) problems. Firstly, we summarily introduce the fundamental concepts, operation formulas and distance calculating method of TFNNs. Then we review some aggregation operators of TFNNs. Thereafter, we extend the original VIKOR model to the triangular fuzzy neutrosophic environment and introduce the calculating steps of the TFNNs VIKOR method, our proposed method which is more reasonable and scientific for considering the conflicting criteria. Furthermore, a numerical example for potential evaluation of emerging technology commercialization is presented to illustrate the new method, and some comparisons are also conducted to further illustrate advantages of the new method

Decision-making in fuzzy environment

Decision-making is a logical human judgment process for identifying and choosing alternatives based on the values and preferences of the decision maker that mostly applied in the managerial level of the concerned department of the organization/ supply chain. Recently, decision-making has gained immense popularity in industries because of their global competitiveness and to survive successfully in respective marketplace.Therefore, decision-making plays a vital role especially in purchase department for reducing material costs, minimizing production time as well as improving the quality of product or service. But, in today’s real life problems, decision-makers generally face lot of confusions, ambiguity due to the involvement of uncertainty and subjectivity in complex evaluating criterions of alternatives. To deal such kind of vagueness in human thought the title ‘Decision-Making in Fuzzy Environment’ has focused into the emerging area of research associated with decision sciences. Multiple and conflicting objectives such as ‘minimize cost’ and ‘maximize quality of service’ are the real stuff of the decision-makers’ daily concerns. Keeping this in mind, this thesis introduces innovative decision aid methodologies for an evaluation cum selection policy analysis, based on theory of multi criteria decision-making tools and fuzzy set theory. In the supplier selection policy, emphasis is placed on compromise solution towards the selection of best supplier among a set of alternative candidate suppliers. The nature of supplier selection process is a complex multi-attribute group decision making (MAGDM) problem which deals with both quantitative and qualitative factors may be conflicting in nature as well as contain incomplete and uncertain information. Therefore, an application of VIKOR method combined with fuzzy logic has been reported as an efficient approach to support decision-making in supplier selection problems. This dissertation also proposes an integrated model for industrial robot selection considering both objective and subjective criteria’s. The concept of Interval-Valued Fuzzy Numbers (IVFNs) combined with VIKOR method has been adapted in this analysis

Fuzzy belief structure based VIKOR method: an application for ranking delay causes of Tehran metro system by FMEA criteria

Public transport is a critical part of civilization in this decade. The amount of money invested and the criticality of transferring people in an acceptable time and without any conflict made it a challenging problem for managers, especially in metropolises. Absolutely, making effective decisions in this area requires considering different aspects. Waiting time is a key criterion in apprising quality of public transport. In this paper, a real world case study of ranking causes of delay in Tehran (Iran) metro system is solved by developing multi attribute group decision-making VIšeKriterijumska Optimizacija I KOmpromisno Rešenje (in Serbian, VIKOR) method under uncertainty, where this uncertainty is captured by Fuzzy Belief Structures (FBS). The obtained results are then compared with a previously proposed Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method with FBSs. The results show that human related issues, along with the problems related to line and transportation system are the most important causes of delay. The obtained results of the problem seem acceptable for decision makers

Modified EDAS Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making with Interval-valued Intuitionistic Fuzzy Information

The Interval-valued intuitionistic fuzzy sets (IVIFSs) based on the intuitionistic fuzzy sets combines the classical decision method is in its research and application is attracting attention. After comparative analysis, there are multiple classical methods with IVIFSs information have been applied into many practical issues. In this paper, we extended the classical EDAS method based on cumulative prospect theory (CPT) considering the decision makers (DMs) psychological factor under IVIFSs. Taking the fuzzy and uncertain character of the IVIFSs and the psychological preference into consideration, the original EDAS method based on the CPT under IVIFSs (IVIF-CPT-MABAC) method is built for MAGDM issues. Meanwhile, information entropy method is used to evaluate the attribute weight. Finally, a numerical example for project selection of green technology venture capital has been given and some comparisons is used to illustrate advantages of IVIF-CPT-MABAC method and some comparison analysis and sensitivity analysis are applied to prove this new methods effectiveness and stability.Comment: 48 page

The Interval-Valued Intuitionistic Fuzzy MULTIMOORA Method for Group Decision Making in Engineering

Multiple criteria decision making methods have received different extensions under the uncertain environment in recent years. The aim of the current research is to extend the application of the MULTIMOORA method (Multiobjective Optimization by Ratio Analysis plus Full Multiplicative Form) for group decision making in the uncertain environment. Taking into account the advantages of IVIFS (interval-valued intuitionistic fuzzy sets) in handling the problem of uncertainty, the development of the interval-valued intuitionistic fuzzy MULTIMOORA (IVIF-MULTIMOORA) method for group decision making is considered in the paper. Two numerical examples of real-world civil engineering problems are presented, and ranking of the alternatives based on the suggested method is described. The results are then compared to the rankings yielded by some other methods of decision making with IVIF information. The comparison has shown the conformity of the proposed IVIF-MULTIMOORA method with other approaches. The proposed algorithm is favorable because of the abilities of IVIFS to be used for imagination of uncertainty and the MULTIMOORA method to consider three different viewpoints in analyzing engineering decision alternatives

Evaluating Emergency Response Solutions for Sustainable Community Development by Using Fuzzy Multi-Criteria Group Decision Making Approaches: IVDHF-TOPSIS and IVDHF-VIKOR

Emergency management is vital in implementing sustainable community development, for which community planning must include emergency response solutions to potential natural and manmade hazards. To help maintain such solution repository, we investigate effective fuzzy multi-criteria group decision making (FMCGDM) approaches for the complex problems of evaluating alternative emergency response solutions, where weights for decision makers and criteria are unknown due to problem complexity. We employ interval-valued dual hesitant fuzzy (IVDHF) set to address decision hesitancy more effectively. Based on IVDHF assessments, we develop a deviation maximizing model to compute criteria weights and another compatibility maximizing model to calculate weights for decision makers. Then, two ideal-solution-based FMCGDM approaches are proposed: (i) by introducing a synthesized IVDHF group decision matrix into TOPSIS, we develop an IVDHF-TOPSIS approach for fuzzy group settings; (ii) when emphasizing both maximum group utility and minimum individual regret, we extend VIKOR to develop an IVDHF-VIKOR approach, where the derived decision makers’ weights are utilized to obtain group decision matrix and the determined criteria weights are integrated to reflect the relative importance of distances from the compromised ideal solution. Compared with aggregation-operators-based approach, IVDHF-TOPSIS and IVDHF-VIKOR can alleviate information loss and computational complexity. Numerical examples have validated the effectiveness of the proposed approaches

VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications

The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique

Application of Fuzzy Logic on Understanding of Risks in Supply Chain and Supplier Selection

The aim of this research is firstly to determine the key risk factors of Supply Chain Management (SCM) and developing an efficient model to assess them. In this work, first the risks involved in SCM has been identified and arranged in a systematic hierarchical structure. Questionnaire surveys have been used for data collection from a managerial decision-making group of a case industry. Next, based on the obtained linguistic data, a fuzzy logic based assessment module has been designed for the evaluation of aggregated SC risks. Finally, various risk factors have been categorized; then ranked using ‘fuzzy maximizing and minimizing fuzzy set theory’ in order to identify/assess the major risk factors that need to be managed or controlled. The present trend in the market is no longer the competition among the enterprises but the supply chain. Supplier selection is the most critical decision of the whole procuring department. Selection of supplier is a complicated decision involving many criteria to take into consideration. In later part, this study tries to rank the suppliers centred on different risks and draw a compromise solution. In order to achieve this, understanding risks is of utmost important. In this work, risks associated with the supplier selection have been recognized and analyzed to rank candidate suppliers based on their affinity to risk using fuzzy based VIKOR method. These risks have varied probability of occurrence and impact on the supply chain. Risks have been represented by linguistic variables and then parameterized by Triangular Fuzzy Number (TFN). Fuzzy risk extent has been calculated and thereby Fuzzy Best Value (FBV) and Fuzzy Worst Value (FWV) have been determined. Fuzzy Utility value has been calculated and utilizing this, ranking has been made by closeness to FBV and farness to FWV. Best alternative has been preferred by maximizing utility group and minimizing regret group

Integrated evaluation model for surface water quality: a case study in Ho Chi Minh City, Vietnam

The assessment of water quality is an important aspect of environmental management. One method commonly applied is the Water Quality Index. The index consists of a group of experimental formulae used for calculating the overall quality of the water environment. In Vietnam, the water quality index is used to calculate water quality based on nine measured parameters, and was officially sanctioned as the standard method for assessing water quality in 2011. In this study another method, adopting the fuzzy logic concept for calculating water quality, is applied. This method has the advantage of dealing with an unlimited number of quality parameters, and can allocate quality classes by calculating quantitative data obtained through monitoring water quality at a number of monitoring sites. However, the method has some limitations such as data loss during the evaluation, and uncertainties due to the method not considering the overall physical environment of the catchments that feed water into the monitoring sites. Fuzzy comprehensive analysis comprises of two main parts: the fuzzy membership and the weights. This study applied the simplest and most used membership function which is triangular and semi-trapezoidal shape, and three different methods of assigning weights: Entropy, Overweight standard and F-statistic for testing the quality of water in the study area, Ho Chi Minh City, Vietnam in South-East Asia, using the monitored quality dataset in 2015. It showed big differences among the results when tested with different weighting methods which is the uncertainty of the Fuzzy method. Therefore, Geographic Information System (GIS) techniques including computer-based sub-watershed delineation modelling using a geographic hydrological model, and geographical regression models, including Ordinary Least Square and Geographically Weighted Regression models, were applied to reduce the uncertainty in the fuzzy process. Results of this study demonstrate the model’s applicability and capability for use in water quality evaluation. From the results, an integrated assessment comprising fuzzy and GIS methods is developed for better assessment of the water quality and therefore contributing to the better management

Optimization for Decision Making II

In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner