Multi-Criteria Decision Aid (MCDA) or Multi-Criteria Decision Making (MCDM) methods have received much attention from researchers and practitioners in evaluating, assessing and ranking alternatives across diverse industries. Among numerous MCDA/MCDM methods developed to solve real-world decision problems, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily across different application areas. In this paper, we conduct a state-of-the-art literature survey to taxonomize the research on TOPSIS applications and methodologies. The classification scheme for this review contains 266 scholarly papers from 103 journals since the year 2000, separated into nine application areas: (1) Supply Chain Management and Logistics, (2) Design, Engineering and Manufacturing Systems, (3) Business and Marketing Management, (4) Health, Safety and Environment Management, (5) Human Resources Management, (6) Energy Management, (7) Chemical Engineering, (8) Water Resources Management and (9) Other topics. Scholarly papers in the TOPSIS discipline are further interpreted based on (1) publication year, (2) publication journal, (3) authors' nationality and (4) other methods combined or compared with TOPSIS. We end our review paper with recommendations for future research in TOPSIS decision-making that is both forward-looking and practically oriented. This paper provides useful insights into the TOPSIS method and suggests a framework for future attempts in this area for academic researchers and practitioners.

Review: A state-of the-art survey of TOPSIS applications

Despite the importance of decision-making (DM) techniques for construction of effective decision models for supplier selection, there is a lack of a systematic literature review for it. This paper provides a systematic literature review on articles published from 2008 to 2012 on the application of DM techniques for supplier selection. By using a methodological decision analysis in four aspects including decision problems, decision makers, decision environments, and decision approaches, we finally selected and reviewed 123 journal articles. To examine the research trend on uncertain supplier selection, these articles are roughly classified into seven categories according to different uncertainties. Under such classification framework, 26 DM techniques are identified from three perspectives: (1) Multicriteria decision making (MCDM) techniques, (2) Mathematical programming (MP) techniques, and (3) Artificial intelligence (AI) techniques. We reviewed each of the 26 techniques and analyzed the means of integrating these techniques for supplier selection. Our survey provides the recommendation for future research and facilitates knowledge accumulation and creation concerning the application of DM techniques in supplier selection.

Application of decision-making techniques in supplier selection: A systematic review of literature

Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014

An integrated framework for sustainable supplier selection and evaluation in supply chains

Selecting green suppliers based on GSCM practices: Using Fuzzy TOPSIS applied to a Brazilian electronics company

During recent years, how to determine suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of supplier selection is a complex multi-criteria problem including both quantitative and qualitative factors which may be in conflict and may also be uncertain. The VIKOR method was developed to solve multiple criteria decision making (MCDM) problems with conflicting and non-commensurable (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. In this paper, linguistic values are used to assess the ratings and weights for these factors. These linguistic ratings can be expressed in trapezoidal or triangular fuzzy numbers. Then, a hierarchy MCDM model based on fuzzy sets theory and VIKOR method is proposed to deal with the supplier selection problems in the supply chain system. A numerical example is proposed to illustrate an application of the proposed model.

http://www.irantahgig.ir/wp-content/uploads/40055.pdf

Group decision making process for supplier selection with VIKOR under fuzzy environment

Supplier selection is a complex multi-criteria problem including both quantitative and qualitative factors. In order to select the best suppliers it is necessary to make a trade-off between these factors, some of which may be in conflict and may also be uncertain. In this problem if suppliers have capacity or other different constraints, two problems will exist: which suppliers are best and how much should be purchased from each selected supplier. In this paper an integrated approach of multi-attribute utility theory (MAUT) and linear programming (LP) is proposed for rating and choosing the best suppliers and defining the optimum order quantities among selected ones in order to maximize total additive utility. A numerical example is proposed to illustrate an application of the proposed method.

An integrated group decision-making process for supplier selection and order allocation using multi-attribute utility theory and linear programming

Although much has been written about TQM in SMEs, little attention has been paid to the role of external consultant in the successful implementation of a TQM program in this kind of firms. Sometimes there are some candidates and companies have to select the best one. In general, many factors affect this problem which adheres to uncertain and imprecise data, and usually several people from different functional areas of the company are involved in this process. This study aims to improve the quality of decision in this area. In this paper a systematic decision process for selecting external consultant is proposed. The proposed method is based on TOPSIS method in fuzzy environment. Decision criteria are obtained from the nominal group technique (NGT). Additionally, a real case study is presented to illustrate the application of the proposed method.

http://p30bazar.persiangig.com/pdf/62.pdf

TQM consultant selection in SMEs with TOPSIS under fuzzy environment

Despite of many scholars and practitioners recognize the knowledge management implementation in an organizations but insufficient attention has been paid by researchers to select suitable knowledge portal system (KPS) selection. This study develops a Multi Criteria Decision making model based on the fuzzy VIKOR approach to help organizations in selecting KPS. The suitable portal is the critical influential factors on the success of knowledge management (KM) implementation in an organization. Keywords—Knowledge management, Knowledge portal system, Fuzzy VIKOR.

/pdf/a-group-based-fuzzy-mcdm-for-selecting-knowledge-portal-ng1lpwviff.pdf

A Group Based Fuzzy MCDM for Selecting Knowledge Portal System

Technology selection is one of the most important and strategic decisions made in new product development. Companies need to consider product life cycle issues during the technology selection process. Effective strategies for considering life cycle issues and technology selection together during product development have not been fully explored in the existing literature. In this paper, we review the current literature regarding technology selection and life cycle issues. We also propose a decision-making framework using a mathematical programming method to select the best alternative technology and planning and management of the development project. We do this by considering management control actions, product launch time, budget constraints, and sales volume, as well as demand and market requirements during the product life cycle.

http://ieeexplore.ieee.org/iel5/6296788/6304012/06304160.pdf

Amir Sanayei

Papers

Group decision making process for supplier selection with VIKOR under fuzzy environment

An integrated group decision-making process for supplier selection and order allocation using multi-attribute utility theory and linear programming

TQM consultant selection in SMEs with TOPSIS under fuzzy environment

A Group Based Fuzzy MCDM for Selecting Knowledge Portal System

Integrating product life cycle issues in technology selection