{"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.34820/FK2/08AFQK","identifier":"https://doi.org/10.34820/FK2/08AFQK","name":"Interterminal Transport Dataset","creator":[{"name":"NUR ADI, TAUFIK","affiliation":"Telkom University"}],"author":[{"name":"NUR ADI, TAUFIK","affiliation":"Telkom University"}],"datePublished":"2022-04-05","dateModified":"2022-04-05","version":"1","description":["This dataset is artificially generated. It contains container transport data consisting of origin, destination, start time window (in hours), end time window (in hours), time window duration, start time window (in minutes), and end time window (in minutes). The dataset is generated using the following settings: 1. Five locations (terminals) 2. Min. due date = 2, Max. due date = 24 3. Number of trucks = 10 4. Throughput per 6 hours = 7 containers 5. The container movement rate based on: http://dx.doi.org/10.13000/JFMSE.2017.29.2.354"],"keywords":["Computer and Information Science","Engineering","Other"],"citation":[{"@type":"CreativeWork","text":"Adi, T.N.; Iskandar, Y.A.; Bae, H. Interterminal Truck Routing Optimization Using Deep Reinforcement Learning. Sensors 2020, 20, 5794. https://doi.org/10.3390/s20205794","@id":"https://doi.org/10.3390/s20205794","identifier":"https://doi.org/10.3390/s20205794"}],"license":{"@type":"Dataset","text":"CC0","url":"https://creativecommons.org/publicdomain/zero/1.0/"},"includedInDataCatalog":{"@type":"DataCatalog","name":"Telkom University Dataverse","url":"https://dataverse.telkomuniversity.ac.id"},"publisher":{"@type":"Organization","name":"Telkom University Dataverse"},"provider":{"@type":"Organization","name":"Telkom University Dataverse"},"distribution":[{"@type":"DataDownload","name":"Datasets_ITTRP.txt","fileFormat":"text/plain","contentSize":8404,"description":"This dataset is artificially generated. It contains container transport data consisting of origin, destination, start time window (in hours), end time window (in hours), time window duration, start time window (in minutes), and end time window (in minutes). \n\nThe dataset is generated using the following settings:\n1. Five locations (terminals)\n2. Min. due date = 2, Max. due date = 24\n3. Number of trucks = 10\n4. Throughput per 6 hours = 7 containers\n5. The container movement rate based on: http://dx.doi.org/10.13000/JFMSE.2017.29.2.354","@id":"https://doi.org/10.34820/FK2/08AFQK/6AAR5R","identifier":"https://doi.org/10.34820/FK2/08AFQK/6AAR5R","contentUrl":"https://dataverse.telkomuniversity.ac.id/api/access/datafile/5290"}]}