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To further improve adaptability, we introduce an adaptive large neighborhood search for dynamic request handling and a dynamic pheromone update mechanism that adjusts to real-time traffic conditions. Extensive experiments on 9 benchmark DVRP instances demonstrate that DG-ACO outperforms baseline algorithms, achieving up to 26.7% reduction in optimal path length and an average of 18.2% improvement in computational efficiency. The results validate the effectiveness of density-guided optimization and highlight the algorithm\u2019s potential for real-time logistics and intelligent transportation systems.<\/jats:p>","DOI":"10.34133\/icomputing.0245","type":"journal-article","created":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T12:37:33Z","timestamp":1762864653000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark_01","source":"Crossref","is-referenced-by-count":0,"title":["Density-Guided Ant Colony Optimization Algorithm for Dynamic Vehicle Routing Problems"],"prefix":"10.34133","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3642-007X","authenticated-orcid":true,"given":"Junfeng","family":"Chen","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence and Automation, \rHohai University, Changzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuqi","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence and Automation, \rHohai University, Changzhou, China."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"221","published-online":{"date-parts":[[2025,11,27]]},"reference":[{"issue":"1","key":"e_1_3_3_2_2","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1287\/mnsc.6.1.80","article-title":"The truck dispatching problem","volume":"6","author":"Dantzig GB","year":"1959","unstructured":"Dantzig GB, Ramser JH. 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