A Parallel Genetic Algorithm for the Open-Shop Scheduling Problem Using Deterministic and Random Moves

Harmanani, Haidar M.; Bou Ghosn, Steve; Drouby, Fouad

dc.contributor.author	Harmanani, Haidar M.
dc.contributor.author	Bou Ghosn, Steve
dc.contributor.author	Drouby, Fouad
dc.date.accessioned	2017-02-21T14:20:14Z
dc.date.available	2017-02-21T14:20:14Z
dc.date.copyright	2016	en_US
dc.date.issued	2017-02-21
dc.identifier.issn	0974-0635	en_US
dc.identifier.uri	http://hdl.handle.net/10725/5260
dc.description.abstract	This paper investigates the use of parallel genetic algorithms in order to solve the open-shop scheduling problem. The method is based on a novel implementation of genetic operators that combines the use of deterministic and random moves. The method is implemented using MPI on a Beowulf cluster. Comparisons using the Taillard benchmarks give favorable results for this algorithm.	en_US
dc.language.iso	en	en_US
dc.title	A Parallel Genetic Algorithm for the Open-Shop Scheduling Problem Using Deterministic and Random Moves	en_US
dc.type	Article	en_US
dc.description.version	Published	en_US
dc.author.school	SAS	en_US
dc.author.idnumber	199490170	en_US
dc.author.department	Computer Science and Mathematics	en_US
dc.description.embargo	N/A	en_US
dc.relation.journal	International Journal of Artificial Intelligence	en_US
dc.journal.volume	14	en_US
dc.journal.issue	1	en_US
dc.article.pages	130-144	en_US
dc.keywords	Open-shop scheduling	en_US
dc.keywords	Parallel genetic algorithms	en_US
dc.identifier.ctation	Ghosn, S. B., Drouby, F., & Harmanani, H. M. (2016). A Parallel Genetic Algorithm for the Open-Shop Scheduling Problem Using Deterministic and Random Moves. International Journal of Artificial Intelligence™, 14(1), 130-144.	en_US
dc.author.email	haidar.harmanani@lau.edu.lb	en_US
dc.identifier.tou	http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php	en_US
dc.identifier.url	http://www.aut.upt.ro/~rprecup/IJAI_28.pdf	en_US
dc.author.affiliation	Lebanese American University	en_US