A New Fuzzy TOPSIS Approach to Personnel Selection with Veto Threshold and Majority Voting Rule

The personal selection, one of the fundamental activities of the human resource management, has as objective to select the most appropriate candidate for the organization. This process is defined as a comparison and decision making process. In this process the human experts have an active participation. It is a tendency to consider this problem of multi-criteria decision making under uncertainty. The present work proposes a new approach for TOPSIS, one of the most used in multi-criteria decision making. This variant is the result of the study and implementation of the fuzzy TOPSIS variant that uses, veto threshold to substitute the positive and negative ideal solutions. The other element used is the rule of the majority vote, used fundamentally in the construction of multi-classifiers to combine the predictions of individual classifiers and to make a consensus classification. In the case of the proposal for the selection of the most appropriate alternative, several distance measure are uses. A computer application was developed, this application receives the configuration of the personal selection problem, evaluates the candidates and ranking using the votes.