Dataset for parallel flow-shop schedulingdoi:10.34820/FK2/0S67CTTelkom University Dataverse2022-09-291DARU KUSUMA, PURBA, 2022, "Dataset for parallel flow-shop scheduling", https://doi.org/10.34820/FK2/0S67CT, Telkom University Dataverse, V1Dataset for parallel flow-shop schedulingdoi:10.34820/FK2/0S67CTDARU KUSUMA, PURBATelkom University DataverseDARU KUSUMA, PURBADARU KUSUMA, PURBA2022-09-29Engineeringoptimization, operations research, flow-shopThis 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.CC0 WaiverP. 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.tabelflowshop.sqlapplication/x-sql