The complexity calculation for group decision making using TOPSIS algorithm

Abstract

The complexity calculation is one of the things to be considered in choosing an algorithm to be applied to a decision support system (DSS). This study analyzes the complexity of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm. This algorithm is applied to the ranking process to resolve the problems associated with Multi-Criteria Decision Making (MCDM). MCDM is used for Group Decision Making (GDM) problems in making a decision. The end output of this study is making DM ranking resulted from decision-making. This problem also produces TOPSIS algorithm complexity used in group decision-making. This algorithm complexity is in the part of attribute normalization and weighting which results in O(n2). Whereas the complexity of a positive-negative ideal solution and V distance to A1, A2, A3, and A4 is O(n) and the algorithm complexity ranking results in O(1).

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