A multicriteria intuitionistic fuzzy group decision making for plant location selection with ELECTRE method (original) (raw)
Related papers
Expert Systems With Applications, 2009
Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain, and is typically a multi-criteria group decision problem. In many practical situations, there usually exists incomplete and uncertain information, and the decision makers cannot easily express their judgments on the candidates with exact and crisp values. Therefore, in this paper an extended VIKOR method for group decision making with intuitionistic fuzzy numbers is proposed to solve the supplier selection problem under incomplete and uncertain information environment. In other researches in this area, the weights of each decision makers and in many of them the weights of criteria are pre-determined, but these weights have been calculated in this paper by using the decision matrix of each decision maker. Also, normalized Hamming distance is proposed to calculate the distance between intuitionistic fuzzy numbers. Finally, a numerical example for supplier selection is given to clarify the main results developed in this paper.
A hybrid intuitionistic fuzzy multi-criteria group decision making approach for supplier selection
Journal of Optimization in Industrial Engineering, 2016
Due to the increasing competition of globalization, selection of the most appropriate supplier is one of the key factors for asupply chain management’s success. Due to conflicting evaluations and insufficient information about the criteria, Intuitionisticfuzzy sets (IFSs) considered as animpressive tool and utilized to specify the relative importance of the criteria. The aim of this paper is to develop a new approach for solving the decision making processes. Thusan intuitionistic fuzzy multi-criteria group decision making approach is proposed. Interval-valued intuitionistic fuzzy ordered weighted aggregation (IIFOWA) is utilized to aggregate individual opinions of decision makers into a group opinion. A linear programming model is used to obtain the weights of the criteria.Then acombined approach based onGRAand TOPSIS method is introduced and applied to the ranking and selection of the alternatives. Finally a numerical example for supplier selection is given to illustrate the feasi...
An extended fuzzy VIKOR for group decision making based on fuzzy distance to supplier selection
Scientia Iranica
Supplier Selection Problem (SSP) has become a critical objective of purchasing departments because of its signi cant e ect on successful logistic and Supply Chain Management (SCM). In real-life situations, SSP parameters are often imprecise, vague, uncertain, or incomplete. In this respect, fuzzy sets theory is the best developed approach to formulate these uncertainties. In this paper, we have extended fuzzy VIKOR using an e cient fuzzy distance measure to solve applicable SSP under group decision-making process. In our study, an e cient fuzzy VIKOR for solving SSP under group decisionmaking process is presented in which decision makers have di erent weights in decisionmaking process and their opinions are collected in the form of linguistic variables. In our methodology, preference ratio method is applied to rank the alternatives. Ultimately, several numerical illustrations and sensitivity analyses are performed to demonstrate the applicability of the proposed method.
Journal of Industrial and Systems Engineering, 2015
Supplier selection can be considered as a complicated multi criteria decision-making problem. In this paper the problem of supplier selection is studied in the presence of conflicting evaluations and insufficient information about the criteria and different attitudes of decision makers towards the risk. Most of fuzzy approaches used in multicriteria group decision making (MCGDM) are non-intuitionistic, which significantly restricts their application areas. Because of considering belongingness and nonbelongingness of the issue in a same time, intuitionistic fuzzy sets can better encounter with a real supplier selection problem. Also to deal with different attitudes of decision makers toward the risk, the proposed approach in this paper employs a new decision function to participate this factor in decision process. In order to integrate fuzzy information, interval-valued intuitionistic fuzzy ordered weighted aggregation (IIFOWA) is applied to aggregate the obtained preferences. The influence of unfair arguments in final results can be reduced by assigning low weights to the "optimistic" or "pessimistic" discretions. Ranking process is based on the two indices, weighted score function and weighted accuracy function. To demonstrate the efficiency of the proposed approach, it is implemented to supplier selection in a project-based company.
2011
Supplier selection is one of the most important activities in supply chain management. Aim of this process is to find suppliers which have the most compatible specifications with buyer`s requirements. This study develops an integrated approach by applying intuitionistic fuzzy set and linear programming technique. It uses two indicators to explain supplier's advantages and their flexibility for providing variant orders. It can be used to select appropriate suppliers in a group decision-making environment. A numerical experiment is given to illustrate application of proposed method.
Supplier selection and evaluation using interval-valued intuitionistic fuzzy AHP method
International Journal of Procurement Management, 2017
Supply chain management (SCM) is one of the most important competitive strategies used by modern enterprises. The main aim of supply chain management is to integrate various suppliers to satisfy market demands. To this end, supplier selection and evaluation plays an important role in establishing an effective supply chain. However, it is a hard problem since supplier selection is typically a multi criteria group decision-making problem involving several conflicting criteria on which decision-maker's knowledge is usually vague and imprecise. The current study proposes an AHP method combined with interval intuitionistic fuzzy set to select appropriate supplier in group decision-making environments. A numerical example for supplier selection has been provided to illustrate application of the proposed interval intuitionistic fuzzy AHP method.
Intuitionistic Fuzzy VIKOR Method for Facility Location Selection Problem
International journal of engineering research and technology, 2020
The selection of a facility location, which is a kind of multi-criteria decision-making (MCDM) problem, should be considered strategically. The purpose of this paper is to demonstrate and validate the application of the intuitionistic fuzzy VIKOR (IF-VIKOR) method to solve one problem of realtime location selection of facilities, in which the criteria values are described in exact (crisp) values form. Firstly, the decision matrix is fuzzified and then transformed into an intuitionistic fuzzy decision matrix. The criteria weights are determined using the Intuitionistic fuzzy entropy weight method. Euclidean distance measure is used in this work. The ranking performance of IFVIKOR is discussed and compared with the other conventional MCDM methods obtained by past researchers to assess the impact of the IFVIKOR method. It is observed that the ranking largely remains unchanged in almost all the applied methods and the first two top alternatives exactly match with those as obtained by th...
Mathematical Problems in Engineering
This paper proposes a new scientific decision framework (SDF) under interval valued intuitionistic fuzzy (IVIF) environment for supplier selection (SS). The framework consists of two phases, where, in the first phase, criteria weights are estimated in a sensible manner using newly proposed IVIF based statistical variance (SV) method and, in the second phase, the suitable supplier is selected using ELECTRE (ELimination and Choice Expressing REality) ranking method under IVIF environment. This method involves three categories of outranking, namely, strong, moderate, and weak. Previous studies on ELECTRE ranking reveal that scholars have only used two categories of outranking, namely, strong and weak, in the formulation of IVIF based ELECTRE, which eventually aggravates fuzziness and vagueness in decision making process due to the potential loss of information. Motivated by this challenge, third outranking category, called moderate, is proposed, which considerably reduces the loss of i...
Intuitionistic fuzzy MOORA for supplier selection
The supplier selection is a critical activity within the administration of the supply chain. It is considered a complex problem given that it involves different aspects such as the alternatives to evaluate, the multiple criteria involved as well as the group of decision makers with different opinions. In this sense, the literature reports several methods to help in this difficult activity of selecting the best supplier. However, there are still some gaps in these methods; therefore, it is imperative to further develop research. Thus, the purpose of this paper is to report a hybrid method between MOORA and intuitionistic fuzzy sets for the selection of suppliers with a focus on multi-criteria and multi-group environment. The importance of decision makers, criteria and alternatives are evaluated in terms of intuitionistic fuzzy sets. Then, MOORA is used in order to determine the best supplier. An experimental case is developed in order to explain the proposed method in detail and to demonstrate its practicality and effectiveness.
Expert Systems with Applications, 2015
The current complexity of supply chains (SC) activities requires the need for coordination between supply chains partners to maximize the efficiency. Considered by practitioners as one of the main SC coordination problems, this paper considers the strategic supplier selection problem. Fuzzy set is used in order to address the imprecision of supply chain partners in formulating the preferences values of various selection criteria. The problem is formulated as a multi-stakeholder multi-criteria (MSMC) decision making problem and solved using two novel approaches. The first hybrid approach combines the fuzzy consensus-based possibility measure and fuzzy TOPSIS method. The second hybrid approach combines the fuzzy consensus-based neat OWA and goal programming model where, the inclusion and participation of stakeholders in the decision-making process is explicit. For each approach, the correlation coefficient and standard deviation (CCSD) based objective weight determination model is used to compute the criteria weights. To demonstrate the applicability of the proposed approaches, a simple example of strategic supplier selection problem is presented and the numerical results analyzed. Moreover, for each approach, the deviations between individual solutions and collective solution are evaluated using the Levenshtein distance. Finally, the advantages and disadvantages of each approach are listed.