一种基于排序蚁群算法的物流车多服务方案规划方法
By generating multiple equivalent optimal logistics vehicle scheduling schemes using the sorting ant colony algorithm, the limitations of the single optimal scheme in existing technologies are overcome, and diversified route selection is achieved under the premise of minimum cost, thereby improving the flexibility and robustness of logistics scheduling.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING UNIV OF INFORMATION SCI & TECH
- Filing Date
- 2026-05-11
- Publication Date
- 2026-07-17
AI Technical Summary
Existing logistics optimization technologies only provide a single optimal solution, which cannot meet the dynamic, flexible, and robust requirements of modern smart logistics, leading to increased transportation costs.
A multi-service scheme planning method for logistics vehicles based on the sorting ant colony algorithm is adopted. Through dynamic sub-ant colony size update, key service sequence mining and pheromone matrix matching, multiple equally optimal schemes with the same cost but different service orders are generated.
While ensuring the lowest possible transportation costs, we provide diverse and optimal logistics solutions to improve scheduling efficiency and system fault tolerance, and meet the high robustness requirements of complex logistics scenarios.
Smart Images
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