Static and Dynamic Parameter Settings of Accelerated Particle Swarm Optimisation for Solving Course Scheduling Problem

Autor:	Pupong Pongcharoen, Saisumpan Sooncharoen, Thatchai Thepphakorn
Rok vydání:	2020
Předmět:	Mathematical optimization Polynomial Job shop scheduling Computer science Scheduling (production processes) Particle swarm optimization Swarm behaviour Metaheuristic Confidence interval Course (navigation)
Zdroj:	Lecture Notes in Computer Science ISBN: 9783030608156 CDVE
DOI:	10.1007/978-3-030-60816-3_40
Popis:	The university course timetabling problem (UCTP) is one of the most challenging scheduling problems and also classified to be a Non-deterministic Polynomial (NP)-hard problem. An Accelerated Particle Swarm Optimisation based Timetabling (APSOT) program was developed to generate the best-so-far timetables with the minimal total operating costs. Two new variants of Accelerated Particle Swarm Optimisation (APSO) including Static and Dynamic (S-APSO and D-APSO) were proposed and embedded into the APSOT tool. The analysis of variance on the experimental results indicated that the main effects and interactions of D-APSO were statistically significant with a 95% confidence interval. The S-APSO and Maurice Clerc PSO (MCPSO) outperformed the other variants of PSO for most datasets whereas the execute times required by all variants of PSO were slightly different.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cc06a56d047453f9b316cabaf1100f24 https://doi.org/10.1007/978-3-030-60816-3_40 Zobrazit plný text záznamu