Cloud Service Selection Using Multicriteria Decision Analysis

Table 1

Summary of MCDA techniques and capabilities.

Name	Objective	Criteria/approach	Author and year
Goal programming	Application of linear programming to solve problems relating to multiple and conflicting objects	Combination of the logic of optimization with mathematical programming	Charnes et al. (1955)
Fuzzy	Evaluation of significance weights in terms of linguistic values represented by fuzzy numbers	Linguistic variables used to describe fuzzy terms that are then mapped to numerical variables	Zadeh (1965)
DEMATEL	Construction of a structural model involving associations of complex factors	Numerical contextual relations among the elements representing the power of influence	Gabus and Fontela (1973)
DEA	Evaluation of the competence of an observation relative to a set of similar observations	Mathematical programming	Charnes (1978)
AHP	Pairwise comparison of attributes structured in a hierarchal relationship	Useful technique for hierarchical relationship criteria	Thomas L. Saaty (1980)
PROMETHEE	Similar to ELECTRE but differing in the pairwise comparison stage	Considers the degree to which one alternative differs from another	Brans and Vincke (1980)
TOPSIS	Selection of an alternative simultaneously the closest to the ideal solution and the farthest from the anti-ideal solution	Close to ideal but the farthest from anti-ideal	Hwang and Yoon (1981)
GRA	Solution of problems with complex interrelationships between factors and variables	Based on grey system theory	Deng (1982)
ELECTRE	Pairwise comparison among alternatives used to identify and eliminate alternatives dominated by other alternatives	Checks only whether one alternative is better or worse than the other	Roy (1991)
ANP	More general representation of interrelationships among decision levels and attributes	Unidirectional relationships with dependence and feedback instead of hierarchy	Thomas L. Saaty (1996)
VIKOR	Ranking of compromises representing indices derived from a measure of “closeness” to the “ideal” solution	Employs linear normalization	Opricovic (2004)