Assigning multi-preferences applicants to multi chances based on preference and chance balanced model

Abstract

This study developed a concise but balanced spreadsheet model, and considered both of the preferences of applicants and the fairness among chances. It set two weights in the model, in which one weight is for preference and the second is for chance preference ratio. The purpose can be achieved to maximize the sum of double-weighted score. The model is tested through a case study, which involves 65 applicants and 7 tasks. Each applicant can choose 3 preferred tasks and finally each applicant only be assigned to one task. The double-weighted method is proved to surpass the manual operation and single-weighted (preference) method both in preference success rate index and in average score variance index.