Multi-objective genetic algorithm for competency-based selection of auditing teams

Abstract

To perform an auditing it is necessary to select auditors with certain competences in a given knowledge area. In this work, we present a multi-objective genetic algorithm to select the best auditors to perform a certain auditing. The algorithm involves the competence allocation problem under three different point of views: indispensable competences, dependencies among competences, and auditing budget boundary. We performed a case study where the competence allocation problem is analysed under a combinatorial perspective. The results show that the genetic algorithm proposed reaches better results comparing to random selection method.