Research Article
Bio-inspired algorithm for the Two-Machine Scheduling Problem with a Single Server
@INPROCEEDINGS{10.4108/icst.bict.2014.257914, author={JEAN-PAUL ARNAOUT}, title={Bio-inspired algorithm for the Two-Machine Scheduling Problem with a Single Server}, proceedings={8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)}, publisher={ICST}, proceedings_a={BICT}, year={2015}, month={2}, keywords={ant colony optimization b\&b parallel machines}, doi={10.4108/icst.bict.2014.257914} }- JEAN-PAUL ARNAOUT
Year: 2015
Bio-inspired algorithm for the Two-Machine Scheduling Problem with a Single Server
BICT
ACM
DOI: 10.4108/icst.bict.2014.257914
Abstract
Within the arena of Swarm Intelligence, this research introduces a bio-inspired ant colony optimization (ACO) algorithm for solving the NP-hard Two-Machine Scheduling Problem with a Single Server. The problem consist of a given set of jobs to be scheduled on two identical parallel machines, where each job must be processed on one of the machines, and prior to processing, the job is set up on its machine using one server; the latter is shared between the two machines. ACO performance was compared to the exact solution (B&B), as well as Genetic Algorithm, and the computational results reflected the superiority of ACO in all tested problems. Furthermore, this superiority improved as problem sizes increased, while solving the tested problems within a reasonable computational time.
