Class Schedule Generation using Evolutionary Algorithms

Timetabling problem is known as an NP-hard problem that centres around finding an optimized allocation of subjects onto a finite available number of slots and spaces. It is perhaps the most challenging issues looked by colleges around the globe. Every academic institution faces a problem when prepar...

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Vydáno v:Journal of physics. Conference series Ročník 1950; číslo 1; s. 12067 - 12074
Hlavní autoři: Kakkar, Mohit Kumar, Singla, Jajji, Garg, Neha, Gupta, Gourav, Srivastava, Prateek, Kumar, Ajay
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 01.08.2021
Témata:
Curricula
Evolutionary algorithms
Genetic algorithms
Schedules
Timetables
ISSN:1742-6588, 1742-6596
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Shrnutí:Timetabling problem is known as an NP-hard problem that centres around finding an optimized allocation of subjects onto a finite available number of slots and spaces. It is perhaps the most challenging issues looked by colleges around the globe. Every academic institution faces a problem when preparing courses and exam plans. There are many restrictions raised while preparing a timetable. This paper proposed a method based on the evolutionary algorithms to solve the constrained timetable problem, which helps to create theory as well as lab schedule for universities. A smart adaptive mutation scheme is used to speed up convergence and chromosome format is also problem specific. Here in this paper two algorithms are compared in respect of Timetabling problems. Using GA (Genetic Algorithm) and MA (Memetic algorithm), we optimised the output by selecting the best solution from the available options to present a comprehensive curriculum system.
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ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1950/1/012067