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Part 1: Document Description
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Citation |
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Title: |
Dataset for parallel flow-shop scheduling |
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Identification Number: |
doi:10.34820/FK2/0S67CT |
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Distributor: |
Telkom University Dataverse |
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Date of Distribution: |
2022-09-29 |
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Version: |
1 |
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Bibliographic Citation: |
DARU KUSUMA, PURBA, 2022, "Dataset for parallel flow-shop scheduling", https://doi.org/10.34820/FK2/0S67CT, Telkom University Dataverse, V1 |
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Citation |
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Title: |
Dataset for parallel flow-shop scheduling |
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Identification Number: |
doi:10.34820/FK2/0S67CT |
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Authoring Entity: |
DARU KUSUMA, PURBA (fakultas teknik elektro - rekayasa komputer) |
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Distributor: |
Telkom University Dataverse |
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Access Authority: |
DARU KUSUMA, PURBA |
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Depositor: |
DARU KUSUMA, PURBA |
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Date of Deposit: |
2022-09-29 |
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Study Scope |
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Keywords: |
Engineering, optimization, operations research, flow-shop |
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Abstract: |
This data consists of 40 jobs. Each job will be processed in four stages. The average processing time of each stage is 5 unit time and follows normal distribution. Each data consists of five attributes: job id, stage 1 processing time, stage 2 processing time, stage 3 processing time, and stage 4 processing time. This data is simulation generated data. There are 30 trials. This data contains 1,200 rows. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Bibliographic Citation: |
P. D. Kusuma and A. S. Albana, A Parallel Permutation Flow-Shop Scheduling Model by Using a Two-Step Evolutionary Algorithm to Minimize Intermediate Storage with Tolerable Maximum Completion Time, International Journal of Intelligent Engineering and Systems, 14(6), 2021. |
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Label: |
tabelflowshop.sql |
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Notes: |
application/x-sql |