Multiple Criteria Decision Making (MCDM) is all about making choices in the presence of multiple, generally conflicting criteria. Many reallife problems are multi-objective by nature that requires evaluation of more than one criterion. Therefore, MCDM has become an important issue and many researches are devoted to help people make better decision (Montibeller & Franco, 2011; Wang et al., 2015). However, there is no consensus between authors on classification and categorization of MCDM methods. Vincke (1992) suggest the following categories:(1) multiple attribute theory,(2) outranking methods, and (3) interactive methods. Apart from the above, Carlsson & Fuller (1996) classifies these methods into four quite distinct groups:(1) the outranking methods,(2) the value and utility theory approaches,(3) the interactive multiple objective programming approach, and (4) the methods based on group decision and negotiation theory. Comprehensive reviews of MCDM methods can be found in Figueira et al.(2005), Greco et al.(2010), Zavadskas and Turskis (2011), Liou and Tzeng (2012), Zavadskas et al.(2014) and Mardani et al.(2015), their comparative strengths and weaknesses are presented in Belton & Stewart (2002), Zopounidis and Doumpos (2002) and Zardari et al.(2015).

Following Perny (1998), Fernandez et al.(2010), two main categories of problems can be distinguished: preference oriented problems and similarity oriented problems. In preference oriented problems, the decisionmaker (DM) wants to select the best alternative or rank all the alternatives from best to worst. In these problems, alternatives are evaluated and compared according to a set of criteria. Usually, higher ranking value means a better performance of the alternative, so the alternative with the highest rank can be considered as best