Real Environment-Aware Multisource Data-Associated Cold Chain Logistics Scheduling: A Multiple Population-Based Multiobjective Ant Colony System Approach-Reference-Cited by-同舟云学术

Real Environment-Aware Multisource Data-Associated Cold Chain Logistics Scheduling: A Multiple Population-Based Multiobjective Ant Colony System Approach

Published:2022-12 Issue:12 Volume:23 Page:23613-23627
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Wu Li-Jiao¹,Chen Zong-Gan²^ORCID,Chen Chun-Hua³,Li Yun⁴^ORCID,Jeon Sang-Woon⁵^ORCID,Zhang Jun⁶^ORCID,Zhan Zhi-Hui¹^ORCID

Affiliation:

1. School of Computer Science and Engineering, South China University of Technology, Guangzhou, China

2. School of Computer Science, South China Normal University, Guangzhou, China

3. School of Software Engineering, South China University of Technology, Guangzhou, China

4. Industrial Artificial Intelligence Centre, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China

5. Department of Electronics and Communication Engineering, Hanyang University, Ansan, South Korea

6. Zhejiang Normal University, Jinhua, China

Funder

National Key Research and Development Program of China

National Natural Science Foundations of China

Guangdong Natural Science Foundation

Ministry of Science and Technology of China

Natural Science Foundation of Guangdong Province through ‘Key Project’

National Research Foundation of Korea

Korea Institute of Ocean Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)