Academic Operating Costs Optimisation Using Hybrid MCPSO Based Course Timetabling Tool

Autor:	Saisumpan Sooncharoen, Pupong Pongcharoen, Thatchai Thepphakorn
Rok vydání:	2020
Předmět:	Mathematical optimization Computer science business.industry Particle swarm optimization Local search (optimization) Statistical analysis Timetabling problem business Metaheuristic Swarm intelligence
Zdroj:	Blended Learning. Education in a Smart Learning Environment ISBN: 9783030519674 ICBL
DOI:	10.1007/978-3-030-51968-1_28
Popis:	The course timetabling problem (CTP) is very important for educational institutes. An effective timetable has directly affect to the utilisation of resources and its operating costs. Solving the CTP manually without timetabling tool is extremely difficult, time consuming and may require a group of experts to work for several days. A course timetabling program, named a Hybrid Particle Swarm Optimisation-based Timetabling (HPSOT) tool, has been developed for optimising the academic operating costs. A variant of Particle Swarm Optimisation (PSO) named Maurice Clerc PSO (MCPSO) and its hybridisations with five combinations of insertion operator (IO) and exchange operator (EO) were proposed and embedded in the HPSOT program. The statistical analysis suggested that the results obtained from the hybrid MCPSO were statistically better than those results obtained from the conventional MCPSO for all instances. The average computational times taken by the proposed hybrid methods were quicker than the original MCPSO for all instances.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f30df005cda13d1d4681a4a5260e74fe https://doi.org/10.1007/978-3-030-51968-1_28 Zobrazit plný text záznamu