{"status":"OK","data":{"id":673653,"identifier":"PL3JX3","persistentUrl":"https://doi.org/10.34894/PL3JX3","protocol":"doi","authority":"10.34894","separator":"/","publisher":"DataverseNL","publicationDate":"2026-09-18","storageIdentifier":"surf://10.34894/PL3JX3","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9999,"datasetType":"dataset","locks":[],"latestVersion":{"id":35329,"datasetId":673653,"datasetPersistentId":"doi:10.34894/PL3JX3","datasetType":"dataset","storageIdentifier":"surf://10.34894/PL3JX3","versionNumber":1,"internalVersionNumber":13,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","lastUpdateTime":"2026-09-18T12:26:49Z","releaseTime":"2026-09-18T12:26:49Z","createTime":"2026-09-09T14:07:39Z","publicationDate":"2026-09-18","citationDate":"2026-09-18","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9999,"license":{"name":"CC-BY-NC-4.0","uri":"http://creativecommons.org/licenses/by-nc/4.0","iconUri":"https://i.creativecommons.org/l/by-nc/4.0/88x31.png"},"fileAccessRequest":true,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"Online Meal Delivery Simulator with Courier Behavior and Graph Neural Networks"},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"de Jong, Niels"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"https://ror.org/012p63287","expandedvalue":{"scheme":"http://www.grid.ac/ontology/","termName":"University of Groningen","@type":"https://schema.org/Organization"}},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"0009-0009-0274-1535"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Bakir, Ilke"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"https://ror.org/012p63287","expandedvalue":{"scheme":"http://www.grid.ac/ontology/","termName":"University of Groningen","@type":"https://schema.org/Organization"}},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"0000-0002-3160-526X"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Roodbergen, Kees Jan"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"https://ror.org/012p63287","expandedvalue":{"scheme":"http://www.grid.ac/ontology/","termName":"University of Groningen","@type":"https://schema.org/Organization"}},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"0000-0002-4083-2106"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactName":{"typeName":"datasetContactName","multiple":false,"typeClass":"primitive","value":"Groningen Digital Competence Centre"},"datasetContactAffiliation":{"typeName":"datasetContactAffiliation","multiple":false,"typeClass":"primitive","value":"rug.nl"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"We consider the Meal Delivery Routing Problem (MDRP) faced by online food delivery platforms. In the MDRP, customers’ food orders arrive dynamically throughout the day and must be assigned to autonomous couriers. Each order is prepared at a merchant and must be delivered to a customer by a courier. We develop a polynomial-time heuristic using a Graph Neural Network (GNN) that estimates future assignment costs in a Cost Function Approximation (CFA) framework. To test the performance of our CFA/GNN heuristic, we create an open-source discrete-event simulator for the MDRP, that simulates the delivery of thousands of orders within seconds. We validate our discrete-event simulator on real-world data from Meituan. We train our GNN using policy gradient method. The CFA/GNN heuristic achieves an average click-to-door time reduction of 9.8% to 14.6% compared to a myopic benchmark. Our heuristic handles courier behavior and uncertainty, using bundling and postponement mechanisms, enabling real-time decision-making for online food delivery platforms.  \n<br>\nDataset description:\nThe repository contains C++ files for the compilation of the MeituanSimulator.exe, a discrete event simulator. This simulator can process real-world data from Meituan (see external/Meituan/) and it's output can be examined using a variety of supplied R scripts (see scripts/). We also supply pretrained Graph Neural Network weights (see results/weights/) to enable further research. Detailed descriptions, installation instructions and usage examples can be found in the accompanying README file."}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Business and Management","Social Sciences"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Meal Delivery Routing Problem"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Discrete-event simulator"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Courier Behavior"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Graph Neural Network"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Graph Reinforcement Learning"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Cost Function Approximation"}}]},{"typeName":"distributor","multiple":true,"typeClass":"compound","value":[{"distributorName":{"typeName":"distributorName","multiple":false,"typeClass":"primitive","value":"DataverseNL network"},"distributorAffiliation":{"typeName":"distributorAffiliation","multiple":false,"typeClass":"primitive","value":"DANS"},"distributorAbbreviation":{"typeName":"distributorAbbreviation","multiple":false,"typeClass":"primitive","value":"DVNL"},"distributorURL":{"typeName":"distributorURL","multiple":false,"typeClass":"primitive","value":"https://dataverse.nl/"}}]},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Silva Correia Alves, Ana"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2026-09-09"}]},"dansDataVaultMetadata":{"displayName":"Data Vault Metadata","name":"dansDataVaultMetadata","fields":[{"typeName":"dansDataversePid","multiple":false,"typeClass":"primitive","value":"doi:10.34894/PL3JX3"},{"typeName":"dansDataversePidVersion","multiple":false,"typeClass":"primitive","value":"1.0"},{"typeName":"dansBagId","multiple":false,"typeClass":"primitive","value":"urn:uuid:45016250-37ed-497d-ab44-302418c3338d"},{"typeName":"dansNbn","multiple":false,"typeClass":"primitive","value":"urn:nbn:nl:ui:13-e48043fe-7ca1-4a11-87dc-9252a0d97028"}]}},"files":[{"label":"MeituanSimulator.zip","restricted":false,"version":1,"datasetVersionId":35329,"dataFile":{"id":674207,"persistentId":"","filename":"MeituanSimulator.zip","contentType":"application/zip","friendlyType":"ZIP Archive","filesize":82522248,"storageIdentifier":"surf://store:1a0b446fd5c-0f09956affc8","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"0f22c2db867dfc691889758c435637b10ec7d476"},"tabularData":false,"creationDate":"2026-09-18","publicationDate":"2026-09-18","lastUpdateTime":"2026-09-18T12:26:49Z","fileAccessRequest":true}}]}}}