Real Environment-Aware Multisource Data-Associated Cold Chain Logistics Scheduling: A Multiple Population-Based Multiobjective Ant Colony System Approach
Download
Full text for this resource is not available from the Research Repository.
Export
Wu, Li-Jiao, Chen, Zong-Gan ORCID: 0000-0001-7585-5212, Chen, Chun-Hua ORCID: 0000-0002-4087-5309, Li, Yun ORCID: 0000-0002-6575-1839, Jeon, Sang-Woon ORCID: 0000-0002-0199-2254, Zhang, Jun ORCID: 0000-0003-4148-4294 and Zhan, Zhi-Hui ORCID: 0000-0003-0862-0514 (2022) Real Environment-Aware Multisource Data-Associated Cold Chain Logistics Scheduling: A Multiple Population-Based Multiobjective Ant Colony System Approach. IEEE Transactions on Intelligent Transportation Systems, 23 (12). ISSN 1524-9050
Dimensions Badge
Altmetric Badge
Item type | Article |
URI | https://vuir.vu.edu.au/id/eprint/47261 |
DOI | 10.1109/TITS.2022.3203629 |
Official URL | https://ieeexplore.ieee.org/document/9894366 |
Subjects | Current > FOR (2020) Classification > 4602 Artificial intelligence Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
Keywords | transportation; multiobjective optimization; multisource data association; service quality; personnel; costs |
Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)