A probabilistic partial order theory approach to IT infrastructure selection for Smart Grid

In this research, a multi criteria decision making problem within the Smart Grid has been solved using a modified application of partial order theory (POT), which is an analytical way of dealing with decision making problems. The proposed approach incorporates data of decision matrices as its input. Consequently, by using Monte Carlo simulation, the Ranking Probability Matrix (RPM) is produced which leads us to a total order ranking of the MCDM alternatives. The aim of this paper is to resolve some disadvantages of several conventional methods of determining the best alternative. Thus, the deficiencies of older methods are discussed and their incapability in handling large numbers of alternatives and attributes are resolved. In addition, the uncertainty factor is going to play its role in decision making. We have illustrated the efficiency of our method by implementing it to an IT infrastructure selection problem in Smart Grid.