International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 72 | Issue 10 | Year 2024 | Article Id. IJCTT-V72I10P107 | DOI : https://doi.org/10.14445/22312803/IJCTT-V72I10P107

Optimization of Class Scheduling Problem: A Multi-Constraint Approach for Effective Resource Allocation and Space Utilization

Paulami Bandyopadhyay

Received Revised Accepted Published
22 Aug 2024 26 Sep 2024 11 Oct 2024 23 Oct 2024

Citation :

Paulami Bandyopadhyay, "Optimization of Class Scheduling Problem: A Multi-Constraint Approach for Effective Resource Allocation and Space Utilization," International Journal of Computer Trends and Technology (IJCTT), vol. 72, no. 10, pp. 36-42, 2024. Crossref, https://doi.org/10.14445/22312803/ IJCTT-V72I10P107

Abstract

With the rapid growth of student enrollment and the expansion of academic offerings in universities and colleges worldwide, the task of scheduling classes within existing timetables and facilities has become increasingly complex. Today, class scheduling requires consideration of multiple factors, including room availability, capacity, instructors’ preferences, and more. This problem is considered to be NP-complete and has received some research during the past few years. Several formulations and algorithms have been proposed to solve scheduling problems, most of which are based on local search techniques. In this paper, 2 different types of algorithms have been compared to solve the class scheduling problem: the random restart Hill-Climbing algorithm and the A-Star algorithm.

Keywords

A Star, Class Scheduling, Hill-Climbing, NP-complete, Searching Algorithms.

References

[1] Kian L. Pokorny, and Ryan E. Vincent, “Multiple Constraint Satisfaction Problems Using the A-Star (A*) Search Algorithm: Classroom Scheduling with Preferences,” Journal of Computing Sciences in Colleges, vol. 28, no. 5, pp. 152-159, 2013.
[Google Scholar] [Publisher Link]
[2] Der-Fang Shiau, “A Hybrid Particle Swarm Optimization for a University Course Scheduling Problem with Flexible Preferences,” Expert Systems with Applications, vol. 38, no. 1, pp. 235-248, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Russell, Artificial Intelligence: A Modern Approach, 2nd ed., Pearson Education, 2003.
[Google Scholar] [Publisher Link]
[4] Abdoul Rjoub, “Courses Timetabling Based on Hill Climbing Algorithm,” International Journal of Electrical and Computer Engineering, vol. 10, no. 6, pp. 6558-6573, 2020.
[CrossRef] [Google Scholar] [Publisher Link]