Ranking the Suppliers using a Combined SWARA-FVIKOR Approach

People are evaluating suppliers due to their responsibility which requires the need of a structured process for supplier evaluation. In this paper we used a new model for weighting of criterias and ranking the alternatives. This model is the combination of SWARA (Stepwise weight assessment ratio analysis) and FVIKOR (VlseKriter ijumskaOptimizacija I KompromisnoResenje) methods which evaluate the main criterias based on evaluation of factors that have major impacts on quality of suppliers, and selects the best suppliers according to the criterias. SWARA method is used in determining the weights of the criteria by decision makers and then rankings of the suppliers were determined by Fuzzy VIKOR method. The proposed method in this study is used for ranking the three suppliers of ABZARSAZI in Iran by five indexes that have major impacts on it. For this purpose, in this paper, designed questionnaires are sent to 20 professional experts in different departments of ABZARSAZI COMPANY in Iran for evaluating the criterias using SWARA. The result showed that Delivery is the most important criterias. Such, the results of FVIKOR technique showed that supplier 1 is the best supplier. This proposed approach gives an evaluation method for all of the companies in order to help managers to identify the best suppliers

Ranking of manufacturers of mechanical parts based on a fuzzy multi-criteria decision making method: A case study in Iran National Steel Industrial Group

Considering multiple criteria in evaluating manufacturers, high number of parts, orders and manufacturers for supplying parts of machinery and equipment, selecting the right manufacturer is a serious problem in steel rolling and production factories. The use of Multi-Criteria and methods in decision-making plays an important role in the selection speed and accuracy. Because of multiple criteria in evaluating manufacturers, selecting a limited and effective number of manufacturers seems difficult, so this study aimed to rank potential suppliers in order to identify the best supplier. Decisions in the outsourcing of mechanical parts are made based on multi-criteria methods and grouped decisions. So, this article proposes a method based on the grouped fuzzy decision-making approach in order to evaluate and rank the most suitable suppliers for outsourcing activities in Iran National Steel Industrial Group. Using the proposed method, experts presented their opinions in linguistic words, a range of numbers, deterministic or fuzzy numbers. Then each supplier was ranked based on the model criteria. On this basis, the most effective criteria in selecting companies were also identified

Ranking of manufacturers of mechanical parts based on a fuzzy multi-criteria decision making method: A case study in Iran National Steel Industrial Group

Considering multiple criteria in evaluating manufacturers, high number of parts, orders and manufacturers for supplying parts of machinery and equipment, selecting the right manufacturer is a serious problem in steel rolling and production factories. The use of Multi-Criteria and methods in decision-making plays an important role in the selection speed and accuracy. Because of multiple criteria in evaluating manufacturers, selecting a limited and effective number of manufacturers seems difficult, so this study aimed to rank potential suppliers in order to identify the best supplier. Decisions in the outsourcing of mechanical parts are made based on multi-criteria methods and grouped decisions. So, this article proposes a method based on the grouped fuzzy decision-making approach in order to evaluate and rank the most suitable suppliers for outsourcing activities in Iran National Steel Industrial Group. Using the proposed method, experts presented their opinions in linguistic words, a range of numbers, deterministic or fuzzy numbers. Then each supplier was ranked based on the model criteria. On this basis, the most effective criteria in selecting companies were also identified

Ranking of manufacturers of mechanical parts based on a fuzzy multi-criteria decision making method: A case study in Iran National Steel Industrial Group

Considering multiple criteria in evaluating manufacturers, high number of parts, orders and manufacturers for supplying parts of machinery and equipment, selecting the right manufacturer is a serious problem in steel rolling and production factories. The use of Multi-Criteria and methods in decision-making plays an important role in the selection speed and accuracy. Because of multiple criteria in evaluating manufacturers, selecting a limited and effective number of manufacturers seems difficult, so this study aimed to rank potential suppliers in order to identify the best supplier. Decisions in the outsourcing of mechanical parts are made based on multi-criteria methods and grouped decisions. So, this article proposes a method based on the grouped fuzzy decision-making approach in order to evaluate and rank the most suitable suppliers for outsourcing activities in Iran National Steel Industrial Group. Using the proposed method, experts presented their opinions in linguistic words, a range of numbers, deterministic or fuzzy numbers. Then each supplier was ranked based on the model criteria. On this basis, the most effective criteria in selecting companies were also identified

A Multi-criteria Decision-making Model for Evaluating Suppliers in Green SCM

In order to develop recycle economy and friendly saving environment, many business enterprises have deployed green supply chain management (GSCM) practices. By employing related theorise of GSCM, organizations expect to minimize the environment impact caused by their commercial and industrial activities in supply chain. Different suppliers may provide different GSCM practices, so evaluating their GSCM performance to rank the green suppliers is an important aspect in practice. In this paper, a novel decision method named fuzzy generalized regret decision-making method is proposed. The fuzzy generalized regret decision-making method is based on ordered weighted averaging (OWA) operator, which is used to effectively aggregate individual regrets related to all stats of nature for an alternative under fuzzy decision-making environment. By combing the proposed method with the application background of GSCM practices, a novel fuzzy decision model for evaluating GSCM performance is further proposed. In the proposed model, the regret of decision maker is taken into consideration with an aim of minimizing the dissatisfaction when choosing the best green supplier. Individual regrets related to all criteria for a green supplier are aggregated to obtain effective regret. Finally, the green suppliers can be ranked according to the effective regrets. A numerical example is used to illustrate the effectiveness of the proposed method

Integration of an Improved Grey-Based Method and Fuzzy Multi-Objective Model for Supplier Selection and Order Allocation

For multi-attribute decision making (MADM) problems, a grey based approach (LI) had been developed to evaluate, rank and select the best suppliers. The method calculates a grey possibility degree between compared suppliers alternatives set and positive ideal referential alternative. The drawback of the method is that the negative ideal referential alternative is not considered in evaluating and ranking of the alternatives. Moreover, the method can only consider interval fuzzy number as input data and real number is neglected. Based on this model and other MADM methods, all demand was sold by the best supplier. In other cases, if the best supplier cannot satisfy all demand, multi-objective programming is used to formulate the problem and assign optimum order quantities to the best suppliers (multi-sourcing). Some techniques, such as goal programming (GP) approach, ε-Constraint method, Reservation level (RL) driven Tchebycheff procedure (RLTP) method had been proposed to solve the multi-objective models. It may be a problem that these techniques traced back to more than 10 years ago. Therefore, there may be still the need to produce a new technique in order to solve the multi-objective models. In this study, to overcome the first drawback, the LI method was improved based on the concepts of technique for order preference by similarity to ideal solution (TOPSIS) to consider both the positive and the negative ideal referential alternative for evaluation of the suppliers. The improved version of the LI method is called the I.LI method. Based on the concepts of TOPSIS, the chosen alternative should have the shortest distance from the positive ideal solution and the farthest from the negative ideal solution. Moreover, in order to solve the problems, a new grey based method (NG) based on the TOPSIS concepts was proposed that can easily consider both interval fuzzy number and real number simultaneously. Afterwards, an innovative comparative approach was proposed to compare the three MADM methods, the LI, the I.LI and the NG methods, and to show that which method is more optimal than the other methods. Subsequently, in this thesis, an integration of the NG method and fuzzy multi-objective model was suggested for multi-sourcing and multi-product supplier selection problem. The score of suppliers calculated by the NG method was served as coefficients in one objective function of the multi-objective model. In this fuzzy multi-objective model, the products are divided into two independent and dependent products so that (1) the price breaks (discounts) depend on the size of the order quantities, (2) independent products’ sales volume affect the prices and discounts of the dependent products and (3) all products must be sold as a bundle. Finally, to overcome the third problem, a new weighted additive function, which is able to consider relative importance of each objective as well as condition of fuzzy situation, is proposed to solve the fuzzy multi-objective model and assign optimum order quantities to the suppliers evaluated and ranked by the NG method. The results of the innovative comparative approach showed that the result of the NG method is more optimal than the I.LI method and the latter is more optimal than the LI method. Therefore, the NG method was selected to be integrated with the fuzzy multi-objective model. Also, the fuzzy multi-objective model was solved by the new weighted additive function, and the results demonstrated that besides considering the relative importance of the objectives, the new technique is also able to consider the condition of fuzzy situation

Supplier selection in government organizations based on fuzzy evaluation approach / Fairuz Shohaimay, Nazirah Ramli and Siti Rosiah Mohamed

Asset purchasing is one of the main responsibilities of Information Technology (IT) department which involves selecting the best supplier. The IT department needs to consider many criteria such that the chosen supplier offers the best product and services at acceptable price, without compromising on the quality and standards of goods. Thus, supplier selection is a multi-criteria decision making (MCDM) problem. In real practice, supplier selection is a complex decision making task. The evaluation process of suppliers relies heavily on previous experiences and human judgments which are vague and uncertain. It is relatively difficult for decision makers to provide exact numerical values for the criteria. Hence, fuzzy set theory was introduced to deal with uncertainties and imprecision in linguistic terms values in decision making processes. Although linguistic terms are used in many fuzzy MCDM models, most of the corresponding fuzzy numbers were fixed and taken from the previous literatures. These fuzzy numbers may not necessarily reflect actual respondents' opinions. Therefore, a two-phased fuzzy evaluation technique is proposed in evaluating and selecting suppliers. Firstly, triangular fuzzy numbers were built based on respondents' opinions. Fuzzy evaluation method is used to evaluate the suppliers based on three main criteria and nine sub-criteria. Finally, the suppliers were ranked using distance minimization method

Optimization of the supplier selection process in prefabrication using BIM

Prefabrication offers substantial benefits including reduction in construction waste, material waste, energy use, labor demands, and delivery time, and an improvement in project constructability and cost certainty. As the material cost accounts for nearly 70% of the total cost of the prefabrication project, to select a suitable material supplier plays an important role in such a project. The purpose of this study is to present a method for supporting supplier selection of a prefabrication project. The proposed method consists of three parts. First, a list of assessment criteria was established to evaluate the suitability of supplier alternatives. Second, Building Information Modelling (BIM) was adopted to provide sufficient information about the project requirements and suppliers’ profiles, which facilitates the storage and sharing of information. Finally, the Analytic Hierarchy Process (AHP) was used to rank the importance of the assessment criteria and obtain the score of supplier alternatives. The suppliers were ranked based on the total scores. To illustrate how to use the proposed method, it was applied to a real prefabrication project. The proposed method facilitates the supplier selection process by providing sufficient information in an effective way and by improving the understanding of the project requirements

Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process

The proposed system illustrates that logic fuzzy can be used to aid management in assessing a supplier's environmental performance in the supplier selection process. A user-centred hierarchical system employing scalable fuzzy membership functions implement human priorities in the supplier selection process, with particular focus on a supplier's environmental performance. Traditionally, when evaluating supplier performance, companies have considered criteria such as price, quality, flexibility, etc. These criteria are of varying importance to individual companies pertaining to their own specific objectives. However, with environmental pressures increasing, many companies have begun to give more attention to environmental issues and, in particular, to their suppliers’ environmental performance. The framework presented here was developed to introduce efficiently environmental criteria into the existing supplier selection process and to reflect on its relevant importance to individual companies. The system presented attempts to simulate the human preference given to particular supplier selection criteria with particular focus on environmental issues when considering supplier selection. The system considers environmental data from multiple aspects of a suppliers business, and based on the relevant impact this will have on a Buying Organization, a decision is reached on the suitability of the supplier. This enables a particular supplier's strengths and weaknesses to be considered as well as considering their significance and relevance to the Buying OrganizationPeer reviewe