The optimization model for allocating reward to employees using GAHP and cluster analysis

Classification is one of the important tasks in any work and field. Cluster analysis (CA) is one of the most important classification methods. CA is one of the widely used methods in many scientific fields. Clustering is one of the most popular data mining techniques, and it has many applications in the industry. In the field of human resources management, predefined rules are used to determine the performance and division of employees. The main goal of the current research is to design a suitable model for allocating rewards to employees by using the combined approach of the Group Analytical Hierarchy Process (GAHP) and CA. The research method is practical in terms of purpose and descriptive survey in terms of data collection. For this purpose, first, by designing and distributing a comparative questionnaire of indicators and completing them by the experts of Shahid Fakuri Industries' component manufacturing unit, and by using the group hierarchical analysis process model with Expert Choice software, the weight of the effective indicators in employee evaluation was calculated, then the values of the indicators for ۲۹ employees with using the formula of the normalization function in the Excel software, it is standardized, and the weight of the indicators is multiplied by the standard values of the data, and then the distance matrix and the optimal number of clusters are calculated through the Machaon software, and finally, using the discriminative clustering approach and using the K-means method, data clustering was done with SPSS and Makaon software and a suitable model was presented for allocating rewards to the workers of the parts making unit.

Keywords:

Reward , Employees , CA , GAHP , discriminative clustering , k-means method