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https://rfos.fon.bg.ac.rs/handle/123456789/2770Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Anđelić, Ognjen | - |
| dc.creator | Milošević, Pavle | - |
| dc.creator | Dragović, Ivana | - |
| dc.creator | Rakićević, Zoran | - |
| dc.date.accessioned | 2024-09-24T10:35:45Z | - |
| dc.date.available | 2024-09-24T10:35:45Z | - |
| dc.date.issued | 2024-08 | - |
| dc.identifier.isbn | 978-83-972632-0-8 | - |
| dc.identifier.issn | 2938-5202 | - |
| dc.identifier.uri | https://rfos.fon.bg.ac.rs/handle/123456789/2770 | - |
| dc.description.abstract | This paper proposes a logic-based approach based on Interpolative Boolean Algebra (IBA) for multi-criteria evaluation of different priority and dispatching rules for production scheduling. Scheduling is crucial in optimizing operational activities, enabling efficient resource allocation within specific time constraints. While standard approaches to multi-criteria evaluation often use the weighted sum or weighted product method, they cannot capture logical and statistical relationships from the data. To address these limitations, we propose logical aggregation (LA) based on IBA, ensuring transparency and explainability in data aggregation. This paper evaluates the performance of six well-known priority and dispatching rules on 30 common benchmark instances of the job shop problem based on four scheduling criteria functions as input attributes. Analysis shows that the Critical Ratio rule performs the best, with Earliest Due Date also being a solid recommendation. This is a valuable insight for production managers unable to perform time-consuming simulations when facing tight deadlines. | sr |
| dc.language.iso | en | sr |
| dc.publisher | ISD2024 Proceedings | sr |
| dc.rights | openAccess | sr |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.source | In B. Marcinkowski, A. Przybylek, A. Jarzębowicz, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings). Gdańsk, Poland: University of Gdańsk. ISBN: 978-83-972632-0-8. | sr |
| dc.subject | Scheduling | sr |
| dc.subject | Job shop | sr |
| dc.subject | Interpolative Boolean algebra | sr |
| dc.subject | Logical aggregation | sr |
| dc.subject | Logic-based decision making | sr |
| dc.title | Logic-Based Evaluation Of Production Scheduling Rules Using Interpolative Boolean Algebra | sr |
| dc.type | conferenceObject | sr |
| dc.rights.license | BY | sr |
| dc.identifier.doi | https://doi.org/10.62036/ISD.2024 | - |
| dc.identifier.fulltext | http://prototype2.rcub.bg.ac.rs/bitstream/id/4016/bitstream_4016.pdf | |
| dc.type.version | publishedVersion | sr |
| item.cerifentitytype | Publications | - |
| item.fulltext | With Fulltext | - |
| item.grantfulltext | open | - |
| item.openairetype | conferenceObject | - |
| item.languageiso639-1 | en | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
| Appears in Collections: | Radovi istraživača / Researchers’ publications | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| bitstream_4016.pdf | https://aisel.aisnet.org/isd2014/proceedings2024/datascience/27/ | 394.48 kB | Adobe PDF | ![]() View/Open |
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