On the application of bio-inspired algorithms in timetabling problem

Authors:
Daniela Oliveira Francisco;Ivan Nunes da Silva
Affiliations:
Department of Electrical Engineering, University of São Paulo, São Carlos, SP, Brazil;Department of Electrical Engineering, University of São Paulo, São Carlos, SP, Brazil
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Year:
2012

Citing 5
Cited 0

Self-fertilization based genetic algorithm for university timetabling problem

Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
An informed genetic algorithm for the examination timetabling problem

Applied Soft Computing
Solving University Course Timetabling Problems by a Novel Genetic Algorithm Based on Flow

WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
An informed genetic algorithm for university course and student timetabling problems

ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Automatic timetabling using artificial immune system

AAIM'05 Proceedings of the First international conference on Algorithmic Applications in Management

Quantified Score

Hi-index	0.00

Visualization

Abstract

Timetabling is a classical problem discussed extensively in the literature due to the widespread need for quality timetables. Most educational institutions still prepare their timetables manually, which is a highly time-consuming process and subject to errors. Several approaches to solve this problem are also found in technical studies, which use stochastic search methods due to the problem's complexity. The optimization strategies formulated and compared in this study are based on genetic algorithms and artificial immune systems. The proposed techniques provide quality solutions for the timetabling problem.