Optimization Approach to Multi-Objective Person-Job Fit Job Assignment Problem

Abstract

This paper proposes the mathematical models and optimization approaches for Person-Job (P-J) fit job assignment problem. There are five objectives in this problem. For P-J fit, each employee is assigned to perform a job based on the matching level of his or her competency to that job. The linear membership function is utilized to measure the level of employee's competency that fits to a job. Next, employee satisfaction in terms of job preference list and ranking score is considered. Then, goal programming and fuzzy multi-objective optimization are proposed to provide the appropriate solutions for job assignment. Lingo 15 is used to solve the proposed mathematical models. Decision-makers (DM) can define the weights for goal programming or the shape parameters of exponential membership function to obtain alternative solutions for the job assignment. These enable DM to have sufficient choices in properly making the decision. In conclusion, the proposed mathematical models enhance DM to determine the Person-Job fit job assignment effectively.