A Fuzzy Expert Decision Support System for Job Assignment

Choosing suitable individuals for different positions in an organization has always been one of the most important concerns of management scientists. Several mathematical models have been used to quantify the comparable merits of individuals for different jobs. These are generally developed in a deterministic environment and deal with precise data while evaluating the extent of "merit" falls under a fuzzy environment with completely nonlinear relations between merits and behavioral features of employers. This paper deals with assigning individuals to jobs through designing a fuzzy model as an expert decision support system. To design such model, experimental knowledge of experts is benefited to define the rules. The extreme conditions are used to facilitate and to increase the precisions of experts' judgments. Then through evaluating individuals' scores and applying the obtained results to the fuzzy rule base, fuzzy merits are obtained for different individuals. Finally the linear assignment technique is applied to use the defuzzified merits to achieve an optimal job assignment. An auto after sales services company is considered as a case study.