优化按需食品配送,使用基于BDI的多代理系统和蒙特卡洛树搜索调度
Li Liu1, Shikun Chen2, Huan Jin3
1College of Digital Technology and Engineering, Ningbo University of Finance and Economics, Ningbo, 315175, China.
优化按需食品配送路线至关重要. 具有信念-欲望-意图 (BDI) 和蒙特卡罗树搜索 (MCTS) 的多代理系统 (MAS) 在复杂的交付环境中显著提高了效率和客户满意度.
科学领域:
- 物流和供应链管理的物流和供应链管理.
- 人工智能的人工智能
- 运营研究 运营研究
背景情况:
- 按需食品配送服务在实时路线优化方面面临重大挑战.
- 低效的配送路线会对运营效率和客户满意度产生负面影响.
- 需要先进的决策框架来解决这些复杂问题.
研究的目的:
- 提出和评估一个多代理系统 (MAS),以提高按需食品配送的配送效率.
- 为了比较蒙特卡罗树搜索 (MCTS) 与路线优化插入启发式的性能.
- 证明意图安排方法在改善实时决策方面的有效性.
主要方法:
- 开发一个动态的多代理系统 (MAS),结合信念-欲望-意图 (BDI) 框架.
- 模拟配送平台,乘客和食品机构之间的互动.
- 应用蒙特卡罗树搜索 (MCTS) 和插入启发式算法来优化路线.
主要成果:
- 蒙特卡罗树搜索 (MCTS) 与插入启发式相比表现优越,特别是在复杂的交付场景中.
- 拟议的MAS有效地管理了多个目标,从而提高了服务质量.
- 模拟证实了MCTS在不同条件下优化交付路线的有效性.
结论:
- 先进的意图安排方法,如MCTS,可以显著提高食品交付物流中的实时决策.
- 开发的MAS为提高运营效率和客户满意度提供了可行的解决方案.
- 这项研究有助于智能系统的进步,以实现动态物流的优化.
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