蚁群优化算法
业务
补贴
车辆路径问题
布线(电子设计自动化)
中国
计算机科学
运筹学
经济
工程类
人工智能
计算机网络
地理
市场经济
考古
作者
Wei Hong,Chen Du,Shuling Xu,Xujin Pu
标识
DOI:10.1177/03611981241263343
摘要
This is a study of the two-echelon two-way logistics vehicle routing problem in rural areas while accounting for government subsidies to alleviate the high distribution costs associated with “long transportation chain + low consumption density” in rural logistics. To address the issue, an improved adaptive ant colony optimization (IACO) algorithm was developed and simulations were run to validate it. The experimental findings demonstrate that, in comparison with the conventional adaptive ant colony optimization algorithm method, the IACO algorithm offers superior optimization capabilities. Finally, a case study was conducted in a rural area of China to demonstrate that the two-echelon two-way logistics network outperforms the current single-echelon logistics network by shortening the total driving distance and reducing distribution costs. This research can inform the optimization of rural logistics networks and provide a reference for the rural e-commerce logistics industry.
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