Social networks and genetic algorithms to choose committees with independent members

Abstract

Organizations need representative individuals to make decisions about particular concerns. These representative individuals are appointed in committees, and we expect from his members to make decisions avoiding bias that could arise from closeness between them. In this context, the best committees are those which show the greatest independence between its members. In this work, we present an automatic approach to the committee selection problem. Our aim is to maximize independence among members of the committee. To this end, we propose to build a social network to calculate distances between candidates, and then apply a genetic algorithm to get potential committees with the greatest distances between their members.