Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/5863
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Oğuz, K. | - |
dc.contributor.author | Altuner, B. | - |
dc.contributor.author | Anar, C. | - |
dc.contributor.author | Reisoğlu, E. | - |
dc.contributor.author | Karaca, M.N. | - |
dc.contributor.author | Sevgen, Arya | - |
dc.date.accessioned | 2025-01-25T17:07:20Z | - |
dc.date.available | 2025-01-25T17:07:20Z | - |
dc.date.issued | 2024 | - |
dc.identifier.isbn | 979-835037943-3 | - |
dc.identifier.uri | https://doi.org/10.1109/ASYU62119.2024.10757011 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14365/5863 | - |
dc.description | IEEE SMC; IEEE Turkiye Section | en_US |
dc.description.abstract | We are proposing an evolutionary approach to the identical parallel machine scheduling problem using a novel representation for genetic algorithms. The genetic algorithm is compared to the mathematical model of the problem. Both of the approaches are implemented in Python using related libraries. The results show that, specially for the larger instances of the problem, the genetic algorithm performs better; it finds an appropriate solution with low tardiness values in minutes, rather than hours when the mathematical model is used. Our study shows that genetic algorithms a valid approach for finding solutions to the identical parallel machine scheduling problem. © 2024 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 16 October 2024 through 18 October 2024 -- Ankara -- 204562 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Genetic Algorithm | en_US |
dc.subject | Identical Parallel Machine Scheduling Problem | en_US |
dc.subject | Parallel Machine Scheduling | en_US |
dc.title | Applying Genetic Algorithms To the Identical Parallel Machine Scheduling Problem | en_US |
dc.type | Conference Object | en_US |
dc.identifier.doi | 10.1109/ASYU62119.2024.10757011 | - |
dc.identifier.scopus | 2-s2.0-85213361904 | - |
dc.department | İzmir Ekonomi Üniversitesi | en_US |
dc.authorscopusid | 54902980200 | - |
dc.authorscopusid | 59491601100 | - |
dc.authorscopusid | 59491388600 | - |
dc.authorscopusid | 59490105100 | - |
dc.authorscopusid | 59490105200 | - |
dc.authorscopusid | 59491388700 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | N/A | - |
dc.identifier.wosquality | N/A | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.openairetype | Conference Object | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
crisitem.author.dept | 05.05. Computer Engineering | - |
crisitem.author.dept | 05.09. Industrial Engineering | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
CORE Recommender
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.