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Student selection and assignment methodology based on fuzzy MULTIMOORA and multichoice goal programming
Author(s) -
Deliktas Derya,
Ustun Ozden
Publication year - 2017
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12185
Subject(s) - ranking (information retrieval) , goal programming , conic section , selection (genetic algorithm) , preference , fuzzy logic , computer science , set (abstract data type) , mathematical optimization , function (biology) , operations research , linear programming , mathematics , artificial intelligence , statistics , geometry , evolutionary biology , biology , programming language
Student selection is a multicriteria decision‐making problem that includes both tangible and intangible factors. In these problems if educational institutions have budget or other different constraints, two problems will exist: which students are the best and how students are assigned to the predefined programs? In this study, an integrated approach of fuzzy MULTIMOORA and multichoice conic goal programming is proposed to consider criteria in choosing the best students and define the optimum assignments among the predefined programs to maximize both the total preference value and total ranking value. The rankings of the students are determined by using fuzzy MULTIMOORA. The rankings of candidates are set as the parameters of the first objective function. The placement preferences of the students according to the predefined programs are considered in the second objective function. The candidates are assigned to their placement preferences both by using multichoice conic goal programming among partner universities according to the objectives and by considering the budget and quota.