Process equipment failures (PEFs) are recognized as one of the leading causes of process accidents. Failure modes and effect analysis (FMEA) as a risk assessment technique, has widely been used in a variety of process industries. The conventional form of FMEA uses three parameters of severity (S), occurrence (O), and detection (D) as risk factors to calculate a risk priority number (R.P.N) and rank the failure modes based on this number. But several shortcomings associated with the FMEA have limited its applicability. This study aims at the development of an extension of FMEA that could efficiently handle the vagueness and uncertainty exists in the experts’ judgments in process of failure modes ranking in conventional FMEA. In this paper we used the concept of the Z number to capture the inherent uncertainty exists in the experts’ judgments. In addition, we used Shannon entropy concept to deploy objective weights to adjust subjective weights assigned by experts. Furthermore, the fuzzy VIKOR technique applied to rank and prioritize the failure modes based on the minimum individual regret and the maxi group utility. A numerical example is presented to illustrate an application of the proposed method in a geothermal power plant (GPP). Results are also compared with the conventional FMEA. A sensitivity analysis was conducted to validate the obtained results. Findings indicate that the application of the proposed approach (subjective-objective ranking) in fuzzy environment can improve the applicability of the conventional FMEA method.
The VIKOR method was developed to solve MCDM problems with conflicting and noncommensurable (different units) criteria, assuming that compromising is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria, and on proposing compromise solution (one or more). The VIKOR method is extended with a stability analysis determining the weight stability intervals and with trade-offs analysis. The extended VIKOR method is compared with three multicriteria decision making methods: TOPSIS, PROMETHEE, and ELECTRE. A numerical example illustrates an application of the VIKOR method, and the results by all four considered methods are compared.
► The Fuzzy VIKOR method solves fuzzy multicriteria problem. ► A ranking fuzzy merit represents distance of alternatives to the ideal solution. The fuzzy VIKOR method has been developed to solve fuzzy multicriteria problem with conflicting and noncommensurable (different units) criteria. This method solves problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to handle imprecise numerical quantities. Fuzzy VIKOR is based on the aggregating fuzzy merit that represents distance of an alternative to the ideal solution. The fuzzy operations and procedures for ranking fuzzy numbers are used in developing the fuzzy VIKOR algorithm. VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria, and on proposing compromise solution (one or more). It is extended with a trade-offs analysis. A numerical example illustrates an application to water resources planning, utilizing the presented methodology to study the development of a reservoir system for the storage of surface flows of the Mlava River and its tributaries for regional water supply. A comparative analysis of results by fuzzy VIKOR and few different approaches is presented.
The hesitant fuzzy linguistic term set (HFLTS) has turned out to be a powerful and flexible technique in representing decision makers' qualitative assessments in the processes of decision making. The aim of this paper is to develop a method to solve the multicriteria decision making (MCDM) problem within the context of HFLTS in which the criteria conflict with each other. To do so, the concepts of ideal solutions for a HFL-MCDM problem have been introduced. In addition, in order to represent the closeness of one solution to the ideal one, we propose a sort of hesitant fuzzy linguistic measures, such as the hesitant fuzzy linguistic group utility measure, the hesitant fuzzy linguistic individual regret measure, and the hesitant fuzzy linguistic compromise measure. Based on these measures, we develop a hesitant fuzzy linguistic VIKOR (HFL-VIKOR) method, which is motivated by the traditional VIKOR method. The general procedures for the HFL-VIKOR method are given. Some numerical examples are provided to demonstrate the advantages and practicality of our method. Finally, we make some discussions on the advantages of the HFL-VIKOR method, as well as future work.
Multiple criteria decision making (MCDM) methods provide an effective means of assisting decision makers to choose the best alternative given multiple criteria. The VIKOR method, among others, is characterized by a trade-off between the maximum group utility of the majority (aggregation of all criteria) and the minimum individual regret of the opponent (each of criteria). In this paper, we propose a new VIKOR method that makes use of incomplete criteria weights instead of previous weighting methods such as entropy for objective weights, and equal, analytic hierarchy process (AHP), or fuzzy for subjective weights. The proposed VIKOR method ranks alternatives using the aggregated scores of alternatives computed by multiplying the extreme points of a set of criteria weights by the precise or interval consequences of alternatives. Further, we show that the VIKOR method combines both the expected opportunity loss and the minimax regret by reinterpreting it in terms of a decision making under uncertainty (DMUU) approach. Therefore, the VIKOR method, a well-known MCDM method, can be used for prioritizing strategies under states of nature.
The decision of strategic information system/information technology (IS/IT) outsourcing requires close attention to the evaluation of supplier/vendor selection process because the selection decision involves conflicting multiple criteria and is replete with complex decision-making problems. Selecting the most appropriate suppliers/vendors is considered an important strategic decision that may impact the performance of outsourcing engagements. The purpose of this study is to provide a more efficient delivery approach for evaluating and assessing possible suppliers/vendors. Using the fuzzy VIKOR method, this study provides a rational and systematic process for developing the best alternative and compromise solution under each of the selection criteria. The study's finding offers an important reference for resolving fuzzy multi-criteria decision-making problems.
► The VIKOR method was developed to solve MCDM problems with conflicting and non-commensurable criteria assuming that compromising is acceptable to resolve conflicts. ► The decision criteria could be extended to include both subjective, set by decision makers, and objective criteria which could be set based on end users’ opinions. ► In this paper, we extended the VIKOR method to support both types of weights using Shannon entropy. Recently, resolving the problem of evaluation and ranking the potential suppliers has become as a key strategic factor for business firms. With the development of intelligent and automated information systems in the information era, the need for more efficient decision making methods is growing. The VIKOR method was developed to solve multiple criteria decision making (MCDM) problems with conflicting and non-commensurable criteria assuming that compromising is acceptable to resolve conflicts. On the other side objective weights based on Shannon entropy concept could be used to regulate subjective weights assigned by decision makers or even taking into account the end-users’ opinions. In this paper, we treat supplier selection as a group multiple criteria decision making (GMCDM) problem and obtain decision makers’ opinions in the form of linguistic terms. Then, these linguistic terms are converted to trapezoidal fuzzy numbers. We extended the VIKOR method with a mechanism to extract and deploy objective weights based on Shannon entropy concept. The final result is obtained through next steps based on factors , and . A numerical example is proposed to illustrate an application of the proposed method.
As companies and organizations have grown to rely on their computer systems and networks, the issue of information security management has become more significant. To maintain their competitiveness, enterprises should safeguard their information and try to eliminate the risk of information being compromised or reduce this risk to an acceptable level. This paper proposes an information security risk-control assessment model that could improve information security for these companies and organizations. We propose an MCDM model combining VIKOR, DEMATEL, and ANP to solve the problem of conflicting criteria that show dependence and feedback. In addition, an empirical application of evaluating the risk controls is used to illustrate the proposed method. The results show that our proposed method can be effective in helping IT managers validate the effectiveness of their risk controls.
Environmentally sustainable activities have received an increasing interest among the firms to improve their practices in the supply chain. Although environmental regulations force firms consider these issues, but, green issues are new, evolving every day, and requires a continuous study in the field to gain a complete understanding of the problems. In this study, we illustrate the case of a laptop manufacturer in Malaysia that pursues to evaluate green supply chain management (GSCM) indicators among its practitioners. This paper develops a quantitative evaluation model to measure the uncertainty of GSCM activities and applies an approach based on Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method which is an extension of intuitionistic fuzzy environment aiming to solve the green multi-criteria decision making (GMCDM) problem. The triangular fuzzy numbers (TFNs) were used to handle imprecise numerical quantities. Then, a hierarchical multiple criteria decision making (MCDM) model was proposed based on fuzzy sets theory and VIKOR method to deal with the problem. The results show the alternative ranks of the four evaluated companies which was based on their performance in GSCM initiatives. The results also indicated that the main criteria of the research ranked as follows respectively: eco-design, green production, green purchasing, green recycling, green transportation and green warehousing. Finally, a comparative analysis of results by fuzzy VIKOR is presented. Additionally the scope for future studies is provided at the end of the paper.
How to select the suitable suppliers in the supply chain is critical for an organization’s success and has attracted much attention of both researchers and practitioners. Supplier selection can be regarded as a complex group multiple criteria decision making problem requiring consideration of a number of alternative suppliers and quantitative and qualitative criteria. Additionally, decision makers cannot easily express their judgments on the alternatives with exact numerical values in many practical situations, and there usually exists uncertain and incomplete assessments. In response, this paper proposes an extended VIKOR method for group multi-criteria supplier selection with interval 2-tuple linguistic information. The feasibility and practicability of the proposed interval 2-tuple linguistic VIKOR (ITL-VIKOR) method are demonstrated through three realistic supplier selection examples and comparisons with the existing approaches. Results show that the ITL-VIKOR method being proposed is more suitable and effective to handle the supplier selection problem under vague, uncertain and incomplete information environment.