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Using this type of prediction, we can obtain a more accurate decision in the following optimization step. Efficient mini-batching gradient and heuristic algorithms are designed to solve the joint order assignment and routing problem of last-mile delivery service. Besides, this paper considers the mutual effect between routing decision and delivery\ntime, and provides the corresponding solution algorithm. In addition, this paper conducts a computational study and finds that the proposed method\u2019s performance has an approximate 5% improvement compared with other methods.<\/jats:p>","DOI":"10.1007\/s40747-021-00293-1","type":"journal-article","created":{"date-parts":[[2021,2,22]],"date-time":"2021-02-22T07:02:51Z","timestamp":1613977371000},"page":"2271-2284","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":56,"title":["Data-driven optimization for last-mile delivery"],"prefix":"10.1007","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0562-1124","authenticated-orcid":false,"given":"Hongrui","family":"Chu","sequence":"first","affiliation":[]},{"given":"Wensi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Pengfei","family":"Bai","sequence":"additional","affiliation":[]},{"given":"Yahong","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,2,22]]},"reference":[{"key":"293_CR1","doi-asserted-by":"publisher","unstructured":"Liu S, He L, and Z.-J, Shen M (2020) On-time last mile delivery: order assignment with travel time predictors. 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