State of art surveys of overviews on MCDM/MADM methods.
Humans make decisions all the time. Decision-making is a very complex and difficult task. During the past decades, operations research (OR) has come a long way as a field that supports scientific management. OR mainly deals with model building and algorithmic optimization procedures that facilitate the analysis of complex real-world problems (Zopounidis, Pardalos 2010). Since von Neumann and Morgenstern (1947) and Savage (1954), this has become the dominant paradigm in decision analysis and decision support in the presence of multiple evaluation dimensions. Traditional OR techniques fit the same purpose: they maximise or minimize a utility function in the presence of constraints. Multi-Criteria Decision Making (MCDM) can be said to be both old and new part of OR, depending on one's frame of reference (Koksalan et al. 2011). MCDM has been one of the fastest growing problem areas in many disciplines. The central problem is how to evaluate a set of alternatives in terms of a number of criteria (Triantaphyllou 2010). Many modern researchers have considered MCDM problems. MCDM refers to making decisions in the presence of multiple, usually conflicting, criteria. The past decades have seen a dramatic increase on all main areas of MCDM:
--Formal models (algorithms, procedures and selection paradigms);
--Evaluation theories (assumptions about values or preferences and structured representations of values or preferences);
--Assessment methodologies (elicitation, estimation and scaling of individuals' preferences, utilities and subjective probabilities in MCDM situations) (Fishburn 1978).
There is no unique and well-defined methodology that one could follow step-by-step from the beginning to the end of a decision aiding process. When dealing with objects that can only be described and compared using several characteristics, aggregation is a major issue: it aims at operating a synthesis of the, usually contradictory, features of the objects, in view of achieving a goal such as choosing among the objects, rank ordering them, sorting them into categories and so on (Bouyssou et al. 2006).
MCDM methods cover a wide range of quite distinct approaches. MCDM methods can be broadly classified into two categories: discrete MCDM or discrete MADM (Multi-attribute Decision Making) and continuous MODM (Multi-Objective Decision Making) methods (Fig. 1). A dictionary definition of a "criterion" is "a means or standard of judging" by which one particular choice or course of action could be judged to be more desirable than another (h). Each problem has multiple, usually conflicting objectives/criteria. Each objective/criterion has a different unit of measurement. MCDM can be perceived as a process of evaluating real-world situations based on various qualitative/quantitative criteria in certain/uncertain/ risky environments in order to find a suitable course of action/choice/strategy/policy among several available options (Raju, Kumar 2013).
[FIGURE 1 OMITTED]
MODM methods are associated with problems where alternatives are non-predetermined and the aim of the problem under consideration is to design the best/optimal alternative by considering a set of well-defined design constraints, a set of quantifiable objectives. Thus, MODM methods deal with the design process and the number of alternatives is infinite (continuous). It is a constant challenge for designers to select the best materials and constructions to satisfy complex design problems (Jahan, Edwards 2013).
MADM art is interrelated with art of the Rational Choice Theory. It assumes that people are motivated by money and by the possibility of making a profit, and this has allowed constructing formal and often predictive models of human behaviour. They act rationally within specific given constraints and based on the information that they have about the conditions under which they are acting. Human actions involve both rational and non-rational elements (Scott 2000). Rational choice theories maintain that individuals must anticipate the outcomes of alternative courses of action and calculate that which will be best for them. As it is not possible for individuals to achieve everything they want, they must also make choices in relation to both their goals and means for attaining these goals. Rational individuals choose the alternative that is likely to give them the greatest satisfaction. Although the expected utility model has many possible founders, Von Neumann and Morgenstern (1947) are usually credited for the first axiomatic foundation of expected utility measurement. Today, the expected utility model is widely used as the normative cornerstone of decision analysis (Keeney, Raiffa 1976).
1. Main ideas of overview
Zavadskas and Turskis (2011) published a review of MCDM methods. This study looks at long known and relatively recently published methods. Liou and Tzeng (2012) published an article, which was intended to review the multi-criteria techniques that Zavadskas and Turskis (2011) did not mention in their article. Lately, Liou (2013) summarized the Tzeng's research work. Therefore, this gave rise to an idea to investigate the existing situation with reviews on MCDM/MADM methods.
Discrete MCDM/MADM methods deal with discrete and predetermined alternatives, which are described by a determined discrete criteria set. The main task is:
--Rational selection among limited number of alternatives;
--Assessment and ranking of limited number of alternatives.
Recently, hundreds of publications have been published to provide information about MCDM methods, their development and application in different fields. This article provides an overview of the publication, which provides an overview of MCDM methods. The research is based on Web of Science database, which is a part of Thomson Reuters Web of Knowledge. The 1970s was an important decade for many seminal works. Foundations of modern MCDM were developed in 1950s and 1960s. Development of MCDM researches accelerated during the 80s and early 90s, and seems to have continued its exponential growth (Koksalan et al. 2011). Fig. 2 provides information about this from databases of reference for review of MCDM methods and their application.
The overview provides systematically classified information on MCDM reviews. They are grouped as shown in Fig. 3:
--Books on MCDM methods (Table 2);
--Articles on multi-criteria methods in scientific journals (Table 3);
--Articles on different MCDM approaches (Table 4);
--Comparative analysis of several MCDM methods (Table 5);
--MCDM review related with individual activity topics (Table 6).
[FIGURE 2 OMITTED]
[FIGURE 3 OMITTED]
2. Main results
Table 1 provides information about the scope of the MCDM methods (Table 1). The total of 71 articles were found on the topic "MCDM review papers" in ISI Web of Science database (December 2013). However, there were only some articles that belonged to few different fields of the research area (Table 1).
The book by Koksalan et al. (2011) provides a brief history of the development of MCDM methods. It briefly describes the development of the area from ancient to modern times. Keeney and Raiffa (1976) formulated the basics of Decision with Multiple Objectives. Hwang and Masud (1979) provided review on development of MODM methods and applications in a relatively short period of time. Later, Hwang and Yoon (1981) reviewed the MADM methods (SAW, TOPSIS, ELECTRE, LINMAP).
Saaty (1980) published a detailed study on the analytic hierarchy process (AHP). Later, Saaty (1996) published a study on the further development of the Analytic Network Process (ANP) method. Zeleny (1982) published a book, which deals with the problem of compromise theory. Hwang and Lin (1987) published a study for Group Decision Making under multi-criteria. Roy (1996) summarized the information on ELECTRE group methods. Seminal studies have been prepared by Belton and Stewart (2002), Gal et al. (2009), Miettinen (2009). Brauers (2004) published a study on the basis of which MOORA and MULTIMOORA methods were developed. A great job was done by Figueira et al. (2005), Ehrgott et al. (2010), editing wide studies in which well-known scientists in this area published individual studies on different classes of MCDM methods.
Valuable studies were published by Triantaphyllou (2000, 2010). Hanne (2009) and Kaliszewski (2010) published a detailed study on soft computing intelligent strategies for Meta MCDM. Apparently, this is only a part of all existing noteworthy studies.
A number of books have been published, which contain detailed information about the MCDM approaches in separate specific areas of research. As an outcome of the development and growing application of MCDM methods, many specific subfields have emerged. Next, some of them are named: Ballestero and Romero (2009) analysed MCDM and its application to economic problems; Peldschus and Zavadskas (1997) analysed an application of discrete matrix games theory in construction and management; Chen and Li (2006) investigated applications of MCDM techniques in environmental management of construction; Zavadskas et al. (1994) applied MCDM in project construction; Venkata (2007) demonstrated how the graph theory and matrix approach as well as fuzzy MADM methods can be effectively used for decision-making in various situations of the manufacturing environment; Koo (2009) presented a study on the development of sustainability assessment model.
Table 3 provides information on reviews of general methods of MCDM. Only some have been listed. A seminal study by Bragge et al. (2012) has been recently published, which was carried out based on bibliometric study of MCDM methods prevalence. A large-scale survey was conducted by Toloie-Eshlaghy and Homayonfar (2011). It gives an overview of about 800 links. Zavadskas and Turskis (2011) provided an overview on MCDM methods based on the traditional classification (Hwang, Yoon 1981).
A number of publications can be found in regional journals, such as Alias et al. (2008), and several publications, which provide an overview on the theory of fuzzy MCDM applications, such as Chu, Lin (2009), El-Wahed (2008) and the analysis and classification of multi-criteria systems.
Significantly more review articles on separate MCDM methods (Table 4) have been published. Kaplinski and Tamosaitiene (2010) reviewed applications of discrete matrix game theory, Behzadian et al. (2010)--PROMETHEE method, and Behzadian et al. (2012)--TOPSIS method. Zopounidis and Doumpos (2002) conducted a review on a multi-criteria classification and sorting. Adler et al. (2002) reviewed the DEA method's applications. Shih (2008) conducted a review on TOPSIS group methods. Ishizaka, Labib (2011) and Ho (2008) publications were devoted to the analysis of AHP method. Jadhav and Rajendra Sonar (2009) overviewed MCDM software packages. Balezentis and Balezentis (2013) published a review article on MULTIMOORA method.
A significantly greater number of publications have been devoted to comparative analysis of separate MCDM methods (Table 5). Opricovic and Tzeng (2004) conducted a benchmarking on TOPSIS and VIKOR methods. Simanaviciene and Ustinovicius (2012) provided a benchmarking on TOPSIS, SAW and COPRAS methods. Podvezko (2011) conducted a comparative study of SAW and COPRAS methods and Podviezko (2012) provided a comparative study on SAW, PROMETHEE, TOPSIS, and COPRAS methods. Albinana and Vila (2012) conducted benchmarking on VIKOR, ELECTRE, COPRAS, and EVAMIX methods. A benchmarking MOORA, AHP, TOPSIS, VIKOR, ELECTRE and PROMETHEE methods has been provided by Chakraborty (2011). Interesting and valuable work in the field of MCDM benchmarking has been performed by Kou et al. (2012), Peng et al. (2011), Balezentis et al. (2012) and Stanujkic et al. (2012). Antucheviciene et al. (2011, 2012) carried out investigation on fuzzy MCDM methods (TOPSIS, VIKOR and COPRAS) and provided a comparative analysis. A large number of valuable works has been conducted, which enables us to evaluate the positive and negative characteristics of different MCDM methods and their ability to help solving real practical problems in different areas.
Reviews on topics of individual activities can be identified into a separate group of reviews on MCDM methods. Ehrgott et al. (2004), Xidonas and Psarras (2009) applied the MCDM methods to portfolio optimization and management; Jahan et al. (2010)--material choosing and screening; Diaz-Balteiro and Romero (2008)--forestry-related decisions; Ananda and Herath (2009)--forest management and planning. Greening and Bernow (2004) applied the MCDM methods to design of Coordinated Energy and Environmental Policy; Moffett and Sarkar (2006)--design of conservation area networks. Kaplinski and Tupenaite (2011) reviewed the latest MCDM applications in modern construction economics. Wang et al. (2009) and Yazdani-Chamzini et al. (2013) reviewed MCDM applications for energy systems assessment. Kaplinski and Peldschus (2011) and Tamosaitiene and Kaplinski (2013) reviewed the applications of MCDM methods in the social sciences; Zavadskas et al. (2008) reviewed the applications of MCDM methods in the area of bridge and road construction; and Huang et al. (2011)--MCDM methods in the social sciences.
The paper presents synopsis of numerous publications, which describe the use of traditional MCDM methods and some of the relatively recently developed methods. However, this review does not cover recent methods that have not yet been reviewed in articles or books. However, it is worth noting that publications reviewed in this article at least allow for a partial representation of the structure of those MCDM methods, which are gaining wider use.
Recently, development of hybrid and modular methods is becoming increasingly important. They are based on previously developed well-known methods, such as TOPSIS, SAW, DEA, AHP, ANP, VIKOR, DEMATEL, DEA, PROMETHEE, ELECTRE and their modification, by applying fuzzy and grey number theory. Relatively recently developed MCDM methods, such as COPRAS, ARAS, MOORA, MULTIMOORA, SWARA and WASPAS are rapidly developed and applied to solve real life problems. In order to help researchers and practitioners interested in hybrid MCDM techniques and applications of hybrid MCDM methods, it is necessary to publish reviews on these issues in future.
Caption: Fig. 1. Broad classification of MCDM methods
Caption: Fig. 2. Number of publications on topic: review papers on MCDM methods (based on ISI Web of Science database)
Caption: Fig. 3. Five-step pyramid of MCDM reviews
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Received 31 December 2012; accepted 31 January 2014
Edmundas Kazimieras ZAVADSKAS, Zenonas TURSKIS, Simona KILDIENE
Department of Construction Technology and Management, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Sauletekio al. 11, 10223 Vilnius, Lithuania
Corresponding author Simona Kildiene
Edmundas Kazimieras ZAVADSKAS. PhD, DSc, h.c.multi. Prof., the Head of the Department of Construction Technology and Management of Vilnius Gediminas Technical University, Lithuania. Senior Research Fellow at the Research Institute of Smart Building Technologies. PhD in Building Structures (1973). Dr Sc. (1987) in Building Technology and Management. A member of Lithuanian and several foreign Academies of Sciences. Doctore Honoris Causa from Poznan, Saint Petersburg and Kiev universities. The Honorary International Chair Professor in the National Taipei University of Technology. A member of international organizations; a member of steering and programme committees at many international conferences; a member of the editorial boards of several research journals; the author and co-author of more than 400 papers and a number of monographs in Lithuanian, English, German and Russian. Editor-in-chief of journals Technological and Economic Development of Economy and Journal of Civil Engineering and Management. Research interests: building technology and management, decision-making theory, automation in design and decision support systems.
Zenonas TURSKIS. PhD from VISI (Vilnius Engineering Construction Institute, former name of Vilnius Gediminas Technical University). He works at the Construction Department of Vilnius Gediminas Technical University. He has more than 100 publications in journals such as International Journal of Information Technology & Decision Making, Economic Research, Journal of Economic Computation and Economic Cybernetics Studies and Research (ECECSR) and more. His research interests include automated programming, technological decision multicriteria evaluation in construction and investment areas.
Simona KILDIENE. PhD student at the Department of Construction Technology and Management of Vilnius Gediminas Technical University, Vilnius, Lithuania. Master of Science (construction engineering), VGTU, 2010. Bachelor of Science (construction management), VGTU, 2008. Research interests include construction economics, construction management, multiple criteria analysis and decision-making theories.
Table. 1. Number of publications by research area MCDM review papers (from database ISI Web of Science) Number of MCDM review papers publications Energy fuels 18 Operations research management science 17 Management 12 Environmental sciences, Ecology 10 Economics 5 Environmental sciences 5 Computer science artificial intelligence 3 Engineering Electrical Electronic 3 Biodiversity Conservation 2 Computer science information systems 2 Ecology 2 Environmental studies 2 Geography 2 Geography physical 2 Agronomy 1 Business 1 Chemistry Physical 1 Computer Science interdisciplinary application 1 Computer Science Software Engineering 1 Computer Science Theory Methods 1 Construction Building Technology 1 Engineering Civil 1 Engineering Industrial 1 Engineering Manufacturing 1 Forestry 1 Forestry 1 Health Care Sciences Service 1 Information Science Library Science 1 Mathematics Applied 1 Metallurgy Metallurgical Engineering 1 Mining Mineral Processing 1 Obstetrics Gynaecology 1 Planning Development 1 Public Environmental Occupational Health 1 Statistics Probability 1 Urban Studies 1 Water Resources 1 Table 2. Books on MCDM methods Reference Considered problem Keeney, Raiffa 1976 Decision with MODM Hwang, Masud 1979 MODM methods Saaty 1980 The analytic hierarchy process Hwang, Yoon 1981 MADM Zeleny 1982 MCDM Hwang, Lin 1987 Group MCDM Zavadskas et al. 1994 Multi-criteria evaluation of projects in construction Roy 1996 Multicriteria methodology for decision aiding Saaty 1996 Decision making with dependence and feedback Peldschus, Zavadskas 1997 Matrix games in building technology and management Triantaphyllou 2000 MCDM methods Belton, Stewart 2002 Multiple criteria decision analysis Figueira et al. (Eds.) 2005 Multiple criteria decision analysis Bouyssou et al. 2006 Evaluation and decision models with multiple criteria: stepping stones for the analyst Chen, Li 2006 Environmental management in construction Kahraman 2008 Fuzzy MCDM Gal et al. 2009 Multi-criteria decision making advances in MCDM models, algorithms, theory and applications Hanne 2009 Intelligent strategies for meta MCDM Koo 2009 Development of sustainability assessment model Miettinen 2009 Nonlinear multi objective optimization Ballestero, Romero 2010 MCDM and its applications to economic problems Ehrgott et al. 2010 Trends in multiple criteria decision analysis Kaliszewski 2010 Soft computing for complex multiple criteria decision making Pedrycz et al. 2010 Decision-making in system project, planning, operation, and control: motivation, objectives, and basic concepts offuzzy MCDM Triantaphyllou 2010 MCDM methods: a comparative study Zopounidis, Pardalos 2010 Multi-criteria analysis Koksalan et al. 2011 MCDM Tzeng, Huang 2011 MADM Doumpos, Grigoroudis 2013 Recent advances in intelligent decision making and presentation of hybrid models and algorithms for preference modelling and optimisation problems Ishizaka, Nemery 2013 Multi-criteria decision analysis Larichev, Olson 2001 Multiple criteria analysis in strategic siting problems Table 3. General reviews on MCDM in articles of scientific journals Reference Considered problem Manouselis, Costopoulou 2007 Analysis and classification of multi-criteria recommender systems El-Wahed 2008 Intelligent fuzzy MCDM Chu, Lin 2009 An extension to fuzzy MCDM Zavadskas, Turskis 2011 Multiple criteria decision making (MCDM) methods in economics Bragge et al. 2012 Scholarly communities of research in multiple criteria decision making: a bibliometric research profiling study Liou, Tzeng 2012 Multiple criteria decision making (MCDM) methods in economics Liou 2013 New concepts and trends of MCDM Aruldoss et al. 2013 A survey on multi criteria decision making methods and its applications Table 4. Overview on application of different MCDM methods Reference Considered problem Adler et al. 2002 Data Envelopment Analysis (DEA) Zopounidis, Doumpos 2002 Multicriteria classification and sorting methods Ho 2008 Integrated analytic hierarchy process Shih 2008 MCDM with an application to group TOPSIS Jadhav, Rajendra Sonar 2009 Software packages Cook, Seiford 2009 Data envelopment analysis (DEA) Kaplinski, Tamosaitiene 2010 Game theory application Behzadian et al. 2010 PROMETHEE Ishizaka, Labib 2011 Analytic hierarchy process Behzadian et al. 2012 A state-of the-art survey of TOPSIS applications Balezentis, T., Applications of the multi criteria Balezentis, A. 2013 decision making method MULTIMOORA Table 5. Comparative analysis of MCDM methods Reference Considered problem Kou et al. 2012 Evaluation of classification algorithms using MCDM and rank correlation Peng et al. 2011 FAMCDM Podvezko 2011 Comparative analysis SAW and COPRAS Antucheviciene et al. 2012 Comparative analysis of FTOPSIS, FVIKOR and COPRAS-F Antucheviciene et al. 2011 Measuring congruence of ranking results applying particular MCDM methods Opricovic, Tzeng 2004 TOPSIS and VIKOR Simanaviciene, TOPSIS, SAW, COPRAS Ustinovicius 2012 Chakraborty 2011 MOORA, AHP, TOPSIS, VIKOR, ELECTRE, PROMETHEE Balezentis et al. 2012 VIKOR, TOPSIS, ARAS Albinana, Vila 2012 VIKOR, ELECTRE, COPRAS, EVAMIX Stanujkic et al. 2012 Comparative analysis of some prominent MCDM methods Table 6. MCDM review on topics of individual activities Reference Considered problem Greening, Bernow 2004 Design of coordinated energy and environmental policies Melo et al. 2009 Facility location and supply chain management Moffett, Sarkar 2006 Design of conservation area networks Ananda, Herath 2009 Forest management and planning Diaz-Balteiro, Romero 2008 Forestry decisions Ehrgott et al. 2004 Portfolio optimization Ho et al. 2010 Supplier evaluation and selection Jahan et al. 2010 Material screening and choosing Xidonas, Psarras 2009 Equity portfolio management Kaplinski, Tupenaite 2011 Modern construction economics Wang et al. 2009 Sustainable energy Kaplinski, Peldschus 2011 Social science Huang et al. 2011 Environmental sciences Zavadskas et al. 2008 Quality in bridges and road construction Yazdani-Chamzini et al. 2013 Selecting the optimal renewable energy Tamosaitiene, Kaplinski 2013 Application of MCDM methods in social sciences Kabir et al. 2013 A review of multi-criteria decision-making methods for infrastructure management
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|Title Annotation:||multi-criteria decision making; multi-attribute decision making|
|Author:||Zavadskas, Edmundas Kazimieras; Turskis, Zenonas; Kildiene, Simona|
|Publication:||Technological and Economic Development of Economy|
|Date:||Mar 1, 2014|
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