Please use this identifier to cite or link to this item:
http://148.72.244.84/xmlui/handle/xmlui/15821Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.date.accessioned | 2025-02-11T09:02:44Z | - |
| dc.date.available | 2025-02-11T09:02:44Z | - |
| dc.date.issued | 2024-04-01 | - |
| dc.identifier.issn | 2958-4612 | - |
| dc.identifier.uri | http://148.72.244.84/xmlui/handle/xmlui/15821 | - |
| dc.description.abstract | In the setting of a single machine, this study suggests approximation localsearch strategies to identify approximate solutions to the multi-objective sequencing problem, where the problem is the total of the four objectives: total completion time ∑Cjj= 1,....,n, total lateness ∑Lj, maximum lateness Lmaxand maximum earliness Emax.Descent Method (DM), Simulated Annealing (SA), and genetic algorithm (GA) are three approximate local search techniques that are computer-implemented Matlab programs. On the basisof the outcomes of computing tests, conclusions are modeled on the effectiveness of the local search techniques | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | University of Diyala | en_US |
| dc.subject | Local search, multi-objective, sequencing, genetic algorithm. | en_US |
| dc.title | Approximate Local Search Methods for Multi-objective Sequencing Problem | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | مجلة ديالى للعلوم الاكاديمية / Academic Science Journal (Acad. Sci. J.) | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 10-718+ (1).pdf | 691.2 kB | Adobe PDF | View/Open |
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