# Development of a Modified Simulated Annealing to School Timetabling Problem

**Year of Publication:**2015

Odeniyi, O A., Omidiora, E O., Olabiyisi, S O., Aluko and J O.. Article: Development of a Modified Simulated Annealing to School Timetabling Problem.

*International Journal of Applied Information Systems*8(2):16-24, January 2015. BibTeX@article{key:article, author = "Odeniyi and O. A. and Omidiora and E. O. and Olabiyisi and S. O. and Aluko and J. O.", title = "Article: Development of a Modified Simulated Annealing to School Timetabling Problem", journal = "International Journal of Applied Information Systems", year = 2015, volume = 8, number = 2, pages = "16-24", month = "January", note = "Published by Foundation of Computer Science, New York, USA" }

### Abstract

This work presents a modified simulated annealing applied to the process of solving a typical high school timetabling problem. Preparation of a high school timetable consists basically of fixing a sequence of meetings between teachers and students in a prefixed period of time in such a way that a certain set of constraints of various types is satisfied. The approach presented in the paper has been successfully used to schedule the first time school timetable of Fakunle Comprehensive High School, Osogbo Nigeria during the 2012/2013 session and it was capable of generating timetables for complex problem instances. A task involving 18 Classes, 45 Teachers and 15 Subjects for Junior Secondary School (JSS) with 3 Levels (JSS 1 to JSS 3), and 6 arms each; and 24 Classes, 77 Teachers and 19 Subjects for Senior Secondary School (SSS), with 3 Levels (SSS 1 to SSS 3), and 8 arms (3 for Science Group, 3 for Commercial Group, and 2 for Art Group), for 6 hours, 5 days respectively. The use of the implemented model resulted in significant time saving in the scheduling of the timetables, and a well spread lessons for the teachers. Also none of the teachers and classes was double booked. It was clearly evident that the developed modified simulated annealing reduces the major weakness of slow convergence (convergence at excessive time) associated with the classical simulated annealing.

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### Keywords

NP-Complete, Constraint Satisfaction, Combinatorial Optimization, Scheduling, Modified Simulated Annealing