Please use this identifier to cite or link to this item:
http://148.72.244.84:8080/xmlui/handle/xmlui/8688Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dhahir A. Abdullah | - |
| dc.date.accessioned | 2023-11-09T06:52:44Z | - |
| dc.date.available | 2023-11-09T06:52:44Z | - |
| dc.date.issued | 2013-01-01 | - |
| dc.identifier.issn | 2222-8373 | - |
| dc.identifier.uri | http://148.72.244.84:8080/xmlui/handle/xmlui/8688 | - |
| dc.description.abstract | Swarm intelligence is the study of collective behavior in decentralized and self-organized systems. Particle swarm optimization algorithm (PSOA) models the exploration of a problem space by a population of agents or particles. In this paper, PSOA is used to reduce the makespan and idle time of jop-shop scheduling problem. The proposed algorithm update the speed (Vik ) and position (Xi k ) depend on local (Pbest ) and global (Gbest ) values, in order to find best solutions. The critical path is found by drawing Gantt chart. | en_US |
| dc.description.sponsorship | https://djps.uodiyala.edu.iq/pages?id=65 | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | university of Diyala | en_US |
| dc.subject | makespan, PSO-practice swarm algorithm, job scheduling problem. | en_US |
| dc.title | Objective Flow-Shop Scheduling Using PSO Algorithm | 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 | |
|---|---|---|---|---|
| 161-175 E.pdf | 452.08 kB | Adobe PDF | View/Open |
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