Open AccessGroup strategy of dissertation defense based on greedy retrospective hybrid algorithm
Author(s) -
Pei Fang Su,
Bing Xue Luo,
Fang Deng,
Ai Xue Xia,
Yan Guo
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1634/1/012077
Subject(s) - backtracking , correctness , computer science , greedy algorithm , tree (set theory) , mathematical optimization , node (physics) , depth first search , order (exchange) , quality (philosophy) , search algorithm , algorithm , mathematics , engineering , mathematical analysis , philosophy , finance , epistemology , economics , structural engineering
Thesis defense is an important link to examine the quality of graduate thesis. In order to ensure the fairness of evaluation, the examiners and students are subject to many restrictions when the thesis defense is grouped. Meanwhile, with the popularization of higher education and the increasing number of graduates, grouping becomes very complicated. This paper designs a paper defense grouping strategy based on greedy backtracking hybrid algorithm. In this paper, the best solution of the group of judges and the group of students is found by using the idea of greed, and then the solution space tree is established. Then combined with the idea of backtracking algorithm, the search was carried out from the root node, and the schemes that did not meet the constraints were eliminated until all the results that met the requirements were found. In this way, a grouping strategy can meet the constraints of the arrangement of thesis defense in universities and improve the efficiency and fairness. Finally, the correctness of the algorithm strategy is verified by experiments.