Proceedings Article10.1109/ITI.2003.1225396
Solving timetable scheduling problem using genetic algorithms
B. Sigl,Marin Golub,Vedran Mornar +2 more
- 16 Jun 2003
- pp 519-524
TL;DR: A genetic algorithm for solving a timetable scheduling problem was tested on small and large instances of the problem and performance was significantly enhanced with modification of basic genetic operators.
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Abstract: A genetic algorithm for solving a timetable scheduling problem is described. The algorithm was tested on small and large instances of the problem. Algorithm performance was significantly enhanced with modification of basic genetic operators. Intelligent operators restrain the creation of new conflicts in the individual and improve the overall algorithm 's behavior.
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Citations
Multiobjective Virtual Machine Placement in Cloud Environment
Amol C. Adamuthe,Rupali M. Pandharpatte,Gopakumaran T. Thampi +2 more
- 15 Nov 2013
TL;DR: All the three algorithms reported good solutions whereas GA and NSGA are subjected to premature convergence and duplicate solutions, while NSGA-II gives good and diversified range of solutions.
55
Fuzzy Genetic Heuristic for University Course Timetable Problem
Arindam Chaudhuri,Kajal De,Netaji Subhas +2 more
- 01 Jan 2010
TL;DR: The proposed technique satisfies all hard constraints of problem and achieves significantly better score in satisfying soft constraints and the reduction computational complexity of the algorithm can be considered as future work for further research.
Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem.
TL;DR: The Genetic Algorithm approach for graph colouring corresponding to the timetable problem is analysed and the improvement of the initial solution is exhibited by the results of the experiments based on the specified constraints and requirements.
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A Compromise Programming for Multi-Objective Task Assignment Problem
TL;DR: In this article, a mathematical model is introduced to assign constrained tasks (the time and required skills) to university lecturers, which is capable of generating a calendar that maximizes faculty expectations.
30
A Study on PSO-Based University Course Timetabling Problem
Sheau Fen Ho Irene,Safaai Deris,Mohd Hashim Siti Zaiton +2 more
- 22 Jan 2009
TL;DR: Experimental results confirm that PSO can solve the timetabling problem with promising result and utilize PSO to solve the discrete problem of University Course Timetable (UCT).
30
References
•Book
Genetic Algorithms
David E. Goldberg,William Shakespeare +1 more
- 01 Jan 2002
TL;DR: The present work expresses the problem as a multi-objective optimization problem and a methodology has been proposed based on multi-objective genetic algo-rithm (MOGA) that exploits the effectiveness of MOGA for searching global optimal solutions in selecting an appropriate image enhancement operator.
17.1K
•Book
Genetic Algorithms + Data Structures = Evolution Programs
Zbigniew Michalewicz
- 01 Jan 1992
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
13.5K
•Book
Handbook of Genetic Algorithms
Lawrence Davis
- 01 Jan 1991
TL;DR: This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems, and introduces the fundamental genetic algorithm (GA), and shows how the basic technique may be applied to a very simple numerical optimisation problem.
8.2K
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