Solving University Scheduling Problem Using Hybrid Approach

In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints...

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Main Authors: Aftab Ahmed Shaikh, Abdul Hussain Shah Bukhari, Zubair Ahmed Memon
Format: Article
Language:English
Published: Mehran University of Engineering and Technology 2011-10-01
Series:Mehran University Research Journal of Engineering and Technology
Subjects:
GA
Online Access:http://publications.muet.edu.pk/research_papers/pdf/pdf169.pdf
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spelling doaj-007e831dfc73438c9ba4228393a5782d2020-11-24T23:53:37ZengMehran University of Engineering and TechnologyMehran University Research Journal of Engineering and Technology0254-78212413-72192011-10-01304613624169Solving University Scheduling Problem Using Hybrid ApproachAftab Ahmed ShaikhAbdul Hussain Shah BukhariZubair Ahmed MemonIn universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm) as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.http://publications.muet.edu.pk/research_papers/pdf/pdf169.pdfCourse Timetabling ProblemGABacktracking Recursive Search.
collection DOAJ
language English
format Article
sources DOAJ
author Aftab Ahmed Shaikh
Abdul Hussain Shah Bukhari
Zubair Ahmed Memon
spellingShingle Aftab Ahmed Shaikh
Abdul Hussain Shah Bukhari
Zubair Ahmed Memon
Solving University Scheduling Problem Using Hybrid Approach
Mehran University Research Journal of Engineering and Technology
Course Timetabling Problem
GA
Backtracking Recursive Search.
author_facet Aftab Ahmed Shaikh
Abdul Hussain Shah Bukhari
Zubair Ahmed Memon
author_sort Aftab Ahmed Shaikh
title Solving University Scheduling Problem Using Hybrid Approach
title_short Solving University Scheduling Problem Using Hybrid Approach
title_full Solving University Scheduling Problem Using Hybrid Approach
title_fullStr Solving University Scheduling Problem Using Hybrid Approach
title_full_unstemmed Solving University Scheduling Problem Using Hybrid Approach
title_sort solving university scheduling problem using hybrid approach
publisher Mehran University of Engineering and Technology
series Mehran University Research Journal of Engineering and Technology
issn 0254-7821
2413-7219
publishDate 2011-10-01
description In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm) as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.
topic Course Timetabling Problem
GA
Backtracking Recursive Search.
url http://publications.muet.edu.pk/research_papers/pdf/pdf169.pdf
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