Review A state-of the-art survey of TOPSIS applications Majid Behzadian a,⇑ , S. Khanmohammadi Otaghsara b , Morteza Yazdani b , Joshua Ignatius c a Industrial Engineering Department, Mehralborz University, Tehran, Iran b Industrial Management Department, Islamic Azad University, Firoozkooh, Iran c School of Mathematical Sciences, Universiti Sains, Malaysia article info Keywords: TOPSIS MCDA MCDM Literature review Application areas abstract 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 deci- sion 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 litera- ture 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 fur- ther 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. Ó 2012 Elsevier Ltd. All rights reserved. 1. Introduction Multiple-criteria decision analysis (MCDA) or Multiple-criteria decision making (MCDM) is a sub-discipline and full-grown branch of operations research that is concerned with designing mathemat- ical and computational tools to support the subjective evaluation of a finite number of decision alternatives under a finite number of performance criteria by a single decision maker or by a group (Lootsma, 1999). MCDA/MCDM uses knowledge from many fields, including mathematics, behavioral decision theory, economics, computer technology, software engineering and information sys- tems. Since the 1960s, MCDA/MCDM has been an active research area and produced many theoretical and applied papers and books (Roy, 2005). MCDA/MCDM methods have been designed to desig- nate a preferred alternative, classify alternatives in a small number of categories, and/or rank alternatives in a subjective preference order. A number of literature review papers, i.e., Behzadian, Kazemzadeh, Aghdasi, and Albadvi (2010) on PROMETHEE and Vaidya and Kumar (2006) and Ho (2008) on AHP, show the vitality of the field and the many methods that have been developed. Among numerous MCDA/MCDM methods developed to solve real-world decision problems, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfacto- rily in diverse application areas. Hwang and Yoon (1981) originally proposed TOPSIS to help select the best alternative with a finite number of criteria. As a well-known classical MCDA/MCDM method, TOPSIS has received much interest from researchers and practitioners. The global interest in the TOPSIS method has expo- nentially grown, which we wish to document in this paper. This paper provides a state-of the-art literature survey on TOP- SIS applications and methodologies. A reference repository has been established based on a classification scheme, which includes 266 papers published in 103 scholarly journals since 2000. Schol- arly papers are further categorized into application areas, publica- tion year, journal name, authors’ nationality, and integrating other MADM/MCDM methods into TOPSIS. Our contributions are three- fold: developing a classification scheme focused on these practical considerations, a structured review that provides a guide to earlier research on the TOPSIS method, and identifying research issues for future investigation. The rest of the paper is organized as follows. Section 2 provides a brief overview and the implementation steps used in TOPSIS. Sec- tion 3 describes the methodology used in the literature review. Section 4 provides the breakdown of the review, which contains 0957-4174/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.eswa.2012.05.056 ⇑ Corresponding author. E-mail address: behzadian_ie@yahoo.com (M. Behzadian). Expert Systems with Applications 39 (2012) 13051–13069 Contents lists available at SciVerse ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa