{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T22:10:35Z","timestamp":1766182235238},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684703","type":"print"},{"value":"9781643684710","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T00:00:00Z","timestamp":1702339200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,12]]},"abstract":"<jats:p>In the field of inventory management, due to the rapid development of artificial intelligence technology, especially data mining and machine learning, new research paradigm has been added to inventory decision-making. Compared with demand forecasting based on sales volume in previous studies, existing research aims to more fully utilize various ancillary information related to products to assist decision-making. In addition, compared with the traditional two-step decision-making (predict first and then optimize), the end-to-end (E2E) proposed in recent years can effectively avoid errors caused by the intermediate process. Based on the idea of E2E, this paper builds an end-to-end integration model E2E-Weighted on how to make optimal ordering decisions for e-commerce companies under the conditions of inventory backlog and service level target constraints. This paper also iteratively developed the model solution method KNN-Weighted based on the KNN algorithm. Results proves that as the number of samples increases, the KNN-Weighted algorithm converges to the theoretical optimal value and is better than other traditional algorithms. Furthermore, the E2E-Weighted model is more suitable for situations with high inventory target service levels.<\/jats:p>","DOI":"10.3233\/faia231080","type":"book-chapter","created":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T15:09:50Z","timestamp":1702566590000},"source":"Crossref","is-referenced-by-count":1,"title":["Data-Driven E-Commerce End-to-End Inventory Optimization Algorithm"],"prefix":"10.3233","author":[{"given":"Qin","family":"Zhang","sequence":"first","affiliation":[{"name":"School of management, Shanghai University, Shanghai 200444, China"}]},{"given":"Yi","family":"Tan","sequence":"additional","affiliation":[{"name":"School of management, Shanghai University, Shanghai 200444, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining IX"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA231080","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T15:09:51Z","timestamp":1702566591000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA231080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,12]]},"ISBN":["9781643684703","9781643684710"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia231080","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,12]]}}}