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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Mortaza Abbaszadeh
Ilkhchi Branch, Islamic Azad University, Ilkhchi, Iran.
Computer Science & IT Engineering

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A Fast Genetic Algorithm for Solving University Scheduling Problem Mortaza Abbaszadeh; Saeed Saeedvand
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 3, No 1: March 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (402.624 KB) | DOI: 10.11591/ijai.v3.i1.pp7-15

Abstract

University course timetabling is a NP-hard problem which is very difficult to solve by conventional methods, we know scheduling problem is one of the Nondeterministic Polynomial (NP) problems. This means, solving NP problems through normal algorithm is a time-consuming process (it takes days or months with available equipment) which makes it impossible to be solved through a normal algorithm like this. In purposed algorithm the problem of university class scheduling is solved through a new chromosome structure and modifying the normal genetic methods which really improves the solution in this case. We include lecturer, class and course information in presented algorithm, with all their Constraints, and it creates optimized scheduling table for weekly program of university after creating primary population of chromosomes and running genetic operators. In the final part of this paper we conclude from the results of input data analysis that the results have high efficiency compared with other algorithms considering maximum Constraints.
Co-Authors Saeed Saeedvand