Human Resource Manager Selection Based on Logarithmic Fuzzy Preference Programming and TOPSIS Methods

Abstract

Today’s organizations must gain competitive advantage through the effective utilization of their human resources. Successful human resource management can contribute to superior performance as a source of competitive advantage by making organizations more effective. The purpose of this paper is applying a new integrated method to Human Resource Manager Selection. Proposed approach is based on Logarithmic fuzzy preference programming and TOPSIS methods. LFPP method is used in determining the weights of the criteria by decision makers and then selecting Human Resource Manager are determined by TOPSIS method. A real case demonstrates the application of the proposed method.