TOPSIS developed by Hwang and Yoon (1981) is a distance-based MCDM method that is used for determining alternatives. TOPSIS is based on choosing the best alternative, which has the shortest distance from the positive-ideal alternative and the longest distance from the negative-ideal alternative (Hwang and Yoon, 1981; Karsak, 2002; Wu et al. 2010). The concept of distance measures, of the alternatives from positive-ideal solution (PIS) and the negative-ideal solution (NIS) proposed by Hwang and Yoon (1981), is the most straightforward technique in MADM (Shih et al. 2007). PIS maximises the benefit criteria and minimises the cost criteria, while the NIS maximises the cost criteria and minimises the benefit criteria (Wang and Elhag, 2006).
The concept of TOPSIS is rational and understandable, and the computation involved is uncomplicated. Moreover, the inherent difficulty of assigning reliable subjective preference to the criteria is worth noting (Shyur, 2006). Although TOPSIS is popularly used to solve MCDM problems, this approach also has some defects (Yu et al. 2011). TOPSIS is often criticised for its inability to deal with vague and uncertain problems (Yu et al. 2011). In many applications, it is difficult to handle ambiguous and vague issues for the method and mathematical models cannot cope with decision-makers‟ ambiguities, uncertainties and vagueness (Chan and Kumar, 2007). In addition, under many conditions crisp data is inadequate to model real-life decision problems. Meanwhile, perfect knowledge is not easily acquired (Kelemenis and Askounis, 2010). Unquantifiable, incomplete and non-obtainable information (Ölçer and Odabsi, 2005) makes precise judgement impossible (Kelemenis and Askounis, 2010).
61
3.4.2.1 TOPSIS Applications
TOPSIS is popularly used by lots of research for four reasons (Shih et al. 2007): 1. TOPSIS logic is rational and understandable;
2. The computation processes are straightforward;
3. The concept permits the pursuit of best alternatives for each criterion depicted in a simple mathematical form; and,
4. The importance weights are incorporated into the comparison procedures.
Table 3.3 TOPSIS applications
Author Application areas No. of attributes No. of alternatives
Yoon and Hwang (1985) Manufacturing plant location analysis 5 major (16 sub-attributes) 5
Parkan and Wu (1999) Robot selection 4 27
Deng et al (2000) Company financial ratios comparison 4 7
Chu (2002a) Facility location selection 5 4
Cheng et al. (2002) Solid waste management 12 11
Janic (2003) High-speed transport system selection 15 3 Cheng and Tzeng (2004) Expatriate host country selection 6 major (25 sub-attributes) 10
Srdjevic et al. (2004) Water management 6 12
Byun and Lee (2005) Rapid prototyping-process selection 6 6
Milani et al. (2005) Gear material selection 5 9
Yang and Chou (2005) Multiple response selection 2 18
Yong (2006) Plant location selection 4 3
Kelemenis and Askounis (2010)
Personnel selection 11 4
Source: Adapted from Shih et al. (2007) and rearranged by author
Due to its logical reasoning, TOPSIS has been used to solve many real-world problems, especially in recent years in the Asian-Pacific region (Shih et al. 2007). Table 3.3 briefly illustrates the various application and the typical areas with the involved attributes and alternatives listed to the corresponding cases. TOPSIS location decision problem can be found in facility location selection (Chu, 2002a, 2002b), and plant location (Yong, 2006). The attributes and the alternatives vary as they are applied to real-life situation, which make them different due to the case-by-case problems. More detail of the TOPSIS application in location decision problem will be discussed in the next section.
62
3.4.2.2 TOPSIS Location Decision Problems
TOPSIS location decision problems has been successfully applied and implemented in site location problems in various fields of study (Chu, 2002a). In this section, the application of TOPSIS combined with AHP will not be mentioned as it already been discussed in Section 3.4.1.2. TOPSIS location decision problems literatures are listed in Appendix D.3.
Karimi et al. (2010) examined the location decision for foreign direct investment in South- East Asian countries using a TOPSIS approach that provides a relatively simple tool for the strategic decision making problem. Fuzzy set theory is widely used in TOPSIS applications, where it has been used to resolve the ambiguity of concepts that are associated with human being‟s judgments (Ertuğrul, 2010). Fuzzy TOPSIS is applicable in fuzzy group decision making for factory facility location selection problem (Ertuğrul, 2010) and in evaluating the location selection of railway passenger station (Liao, 2009). Kucas (2010) combined TOPSIS with Simple Additive Weighting (SAW) for location prioritisation in the case of forest fragmentation-based ranking of forest administrative areas. Bhattacharya et al. (1992, 1993), Boran (2011), and Kuo et al. (2007) studied the alternative location selection with in general with TOPSIS application. Gligorić et al. (2010) integrated fuzzy TOPSIS with Kruskal‟s algorithm and Steiner Points to locate a mine shaft at a deep multiple ore-body deposit. Meanwhile, Safari (2010) applied fuzzy TOPSIS method to locate mineral processing plant site selection in the case of the Sangan, Iran iron ore mine. Fuzzy TOPSIS is useful for manufacturing location selection problem (Chu, 2002a, 2002b; Yong, 2006). Cheng et al. (2002) and Cheng et al. (2003) studied the integration of MCDA and inexact mixed integer linear programming methods to support selection of an optimal landfill site and a waste-flow- allocation pattern such that the total system cost can be minimised. Different multi-objective programming models have been proposed to solve the problem which could minimise the weakness of the method where they are basically mathematical and ignore qualitative and often subjective considerations. Awasthi et al. (2011) presented a fuzzy multi-criteria decision making, TOPSIS, approach for location planning of urban distribution centres under uncertainty. This approach could practically applied by logistics operators in deciding on the location of new distribution centres considering the sustainable freight regulation proposed by municipal administrations. Li et al. (2011) studied the comprehensive method for the selection of logistic centre location. They studied fifteen regional logistics centre cities and thirteen criteria are studied and the numerical result show that the proposed evaluation
63
framework is reasonable to identify logistics centre location, and it is effective to determine the optimal logistics centre location even with the interactive and interdependent criteria and attributes.
It can be seen that the TOPSIS method is applicable to various areas in studies of the location decision problem. TOPSIS is a practical and useful technique for ranking and selection of a number of externally determined alternatives through distance measures. Fuzzy set theory is often incorporated to TOPSIS in evaluating the suitability of alternatives. In the evaluation of the alternative location, quantitative and qualitative assessments are often required to deal with uncertainty, subjective and imprecise data, which are best represented with fuzzy data. This could result effective decision made on the basis of consistent evaluation results.
3.4.2.3 Categorisation of TOPSIS Location Decision Research
This section discusses the distribution of journal articles that are covered in the previous section into articles by journals, country/regional application, and distribution years of the journal papers relate to the research findings.
Appendix D.4 provides the list of journals with the references published in different types of articles. There are a total of seventeen different journals that published location selection related problems that includes TOPSIS. The table demonstrates that the vast majority of the articles (i.e. six articles or 22%) are published in Expert Systems and Applications. The rest are equally spread among the other journals. Looking at the articles published, it can be seen that, generally, the papers that are published in Fuzzy Sets and Systems which often represents the first publication of particular analytical approaches (or combinations of them) in the context of facility location decision problem; such as, Bhattacharya et al. (1992) for TOPSIS.