Open AccessAutomated Timetable Generation
Author(s) -
Prajakta Tanksali,
Ila Dhond,
Shivani Pednekar,
Varshanda Singbal,
Shruti Sivaraman
Publication year - 2020
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit206393
Subject(s) - computer science , workload , operations research , cooperativeness , scheduling (production processes) , heuristic , tardiness , genetic algorithm , operations management , job shop scheduling , artificial intelligence , machine learning , engineering , schedule , psychology , social psychology , temperament , personality , operating system
Timetable generation is a complex job for the administration in terms of time and man power. The system proposed will help to generate it automatically thus saving time. It prevents the complexity of setting and managing Timetable manually. Different algorithms like genetic, heuristic, resource scheduling are used to minimise difficulties faced during generation of timetable. These algorithms consist of a numeral of strategy, aimed to improve the cooperativeness of the search operation. The system will take various inputs like number of subjects, professors, workload of a teacher, semester. Depending on these inputs, timetables for working days of the week for teaching staff will be generated. This will integrate by making optimal use of all the resources in a way that will best suit the constraints.