The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).
If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.
Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.
BibTex Citation Data :
@article{JOIV491, author = {Yosua Halim and Cecilia Nugraheni}, title = {A Bee Colony Algorithm based Solver for Flow Shop Scheduling Problem}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {5}, number = {2}, year = {2021}, keywords = {Scheduling; flow shop scheduling; metaheuristics; Bee Colony Algorithm.}, abstract = {Flow Shop Scheduling (FSS) is scheduled to involve n jobs and m machines in the same process sequence, where each machine processes precisely one job in a certain period. In FSS, when a machine is doing work, other machines cannot do the same job simultaneously. The solution to this problem is the job sequence with minimal total processing time. Many algorithms can be used to determine the order in which the job is performed. In this paper, the algorithm used to solve the flow shop scheduling problem is the bee colony algorithm. The bee colony algorithm is an algorithm that applies the metaheuristic method and performs optimization according to the workings of the bee colony. To measure the performance of this algorithm, we conducted some experiments by using Taillard's Benchmark as problem instances. Based on experiments that have been carried out by changing the existing parameter values, the size of the bee population, the number of iterations, and the limit number of bees can affect the candidate solutions obtained. The limit is a control parameter for a bee when looking for new food sources. The more the number of bees, the more iterations, and the limit used, the better the final time of the sequence of work. The bee colony algorithm can reach the upper limit of the Taillard case in some cases in the number of machines 5 and 20 jobs. The more the number of machines and jobs to optimize, the worse the total processing time.}, issn = {2549-9904}, pages = {170--176}, doi = {10.30630/joiv.5.2.491}, url = {https://joiv.org/index.php/joiv/article/view/491} }
Refworks Citation Data :
@article{{JOIV}{491}, author = {Halim, Y., Nugraheni, C.}, title = {A Bee Colony Algorithm based Solver for Flow Shop Scheduling Problem}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {5}, number = {2}, year = {2021}, doi = {10.30630/joiv.5.2.491}, url = {} }Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
__________________________________________________________________________
JOIV : International Journal on Informatics Visualization
ISSN 2549-9610 (print) | 2549-9904 (online)
Organized by Department of Information Technology - Politeknik Negeri Padang, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
W : http://joiv.org
E : joiv@pnp.ac.id, hidra@pnp.ac.id, rahmat@pnp.ac.id
View JOIV Stats
is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.