Paper Details: Downloads: 605
Serial Number: P1120812020
Title: A Parallel Genetic Algorithm for Solving Time Tabling Problem
Authors: Hossam Faris and Alaa Sheta and Ahmed Tobal
Abstract: As educational institutions are challenged to grow in number and complexity, their resources and events are becoming more harder to schedule. One of the areas of possible improvement in the scheduling process is the task of events timetabling. Timetabling is a kind of problem in which events (exams, classes etc.) have to be arranged into a number of time slots such that conflicts in using a given set of resources are avoided (constraints). In this paper a Parallel Genetic Algorithm (PGA) is used for solving highly constrained timetabling problems. This algorithm runs on a cluster of computing nodes, where each node runs the Genetic Algorithm (GA) on its own isolated subpopulation. These subpopulations exchange their best solutions frequently for a specific time intervals. Experimental results are conducted to show the feasibility and the quality of the timetabling solutions obtained by the proposed genetic approach. We will also study the direct effect of the PGA and the migration process on the fitness value of the generated solutions
Keywords: Parallel Genetic Algorithm, Time Tabling Problem
Journal/Conference: International Journal of Artificial Intelligence and Machine Learning
Volume: 8
Issue: 2
Submission Date: 4/1/2008 12:00:00 AM
Review Date: 6/1/2008 12:00:00 AM
Publishing Date: 9/1/2008 12:00:00 AM
Article Downloads: 605
Download:

Facebook