Title :
Comparing genetic operators for the timetabling problem
Author_Institution :
Dept. of Autom. & Appl. Inf., Budapest Univ. of Technol. & Econ., Budapest, Hungary
Abstract :
This paper describes a genetic algorithm used to solve the timetabling problem. Our approach will deal with the weekly curriculum based timetabling problem using real datasets from the University of Udine. Before proposing an algorithm we examine and compare the performance of the different genetic operators.
Keywords :
educational institutions; genetic algorithms; scheduling; University of Udine; genetic algorithm; genetic operators; weekly curriculum based timetabling problem; Biological cells; Genetic algorithms; Genetics; Optimization; Sociology; Statistics; Testing;
Conference_Titel :
Applied Machine Intelligence and Informatics (SAMI), 2015 IEEE 13th International Symposium on
Conference_Location :
Herl´any
DOI :
10.1109/SAMI.2015.7061845
