一个改进的遗传算法用于解决直升机路由问题,在灾后救援中使用时间窗口
Kaidong Yang1,2, Peng Duan3, Huishan Yu2
1Shandong Key Laboratory of Optical Communication Science and Technology, Liaocheng University, Liaocheng 252059, China.
Mathematical biosciences and engineering : MBE
|November 3, 2023
概括
这项研究优化了直升机发送灾难救援,将其建模为具有时间窗口的车辆路由问题. 一个改进的遗传算法显著减少了直升机的行程距离,提高了救援效率.
科学领域:
- 运营研究 运营研究
- 灾害管理 灾害管理
- 人工智能的人工智能
背景情况:
- 车辆路由问题 (VRP) 在灾后救援行动中至关重要.
- 在灾难应对中使用直升机为有效的派遣带来了重大后勤挑战.
- 现有的方法难以应对时间敏感的直升机路线的复杂性.
研究的目的:
- 为应对在灾后救援中高效发送直升机的挑战.
- 模拟直升机的调度作为车辆路由问题与时间窗口 (VRPTW) 的变体.
- 在灾难场景中开发一个优化的算法来解决VRPTW.
主要方法:
- 开发了一种改进的基因算法 (GA),结合了本地和全球搜索策略.
- 采用了合作初始化策略,以产生高质量,多样化的初始群体.
- 该算法使用来自所罗门实例的56个实例进行了测试.
主要成果:
- 拟议的GA表现出优越的性能,相比Tubu搜索,殖民地优化,混合GA,和模拟化.
- 该算法实现了旅行距离的平均相对百分比增加,比竞争方法要小得多.
- 具体来说,与基准算法相比,拟议的算法减少了0.178,0.027,0.075和0.041倍的行程距离.
结论:
- 开发的改进的GA是解决灾后救援中VRPTW的高效有效方法.
- 该算法成功地减少了直升机驾驶距离,从而提高了救援行动的效率.
- 这项研究为优化在时间关键的灾害响应场景中的资源配置提供了有价值的工具.
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