Assignment model for employing skilled IT professionals for appropriate job roles under uncertainty with different ranking approaches using membership functions

Assignment problems (AP) have a wide range of practical applications because they are widely used in business, management science, and other professions. Due to the inapplicability of traditional and classical APs, particularly complicated real-world issues can be addressed using fuzzy APs which are more effective. Selecting the best candidate for the job can be challenging due to uncertainty and limited data, especially in the IT sector. The AP is one of the most important factors in decision-making for any kind of allocation or assignment. In this article, the assignment model has been employed in order to deal with the job assignment for skilled IT professionals by means of conventional approaches using fuzzy membership functions (FMF) with different ranking methods. Additionally, the model explains the mathematical formulation, outlines, and methodology with numerical illustrations. Moreover, the considered problem is converted into a crisp AP using the different ranking indexes and also the problem has been resolved using the existing traditional assignment methods which enhances the model efficiency. Lastly, the model concludes that the best candidate for the job was recruited and results were compared that the effective application of placement for the right candidate for the right job.