A multi-agent genetic algorithm for multi-period emergency resource scheduling problems in uncertain traffic network

Yawen Zhou, Jing Liu
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引用次数: 2

Abstract

With the frequent occurrence of large-scale disasters, such as landslide and earthquake, timely and effective emergency resource scheduling becomes more and more important. Lots of disasters need multi-period rescue to satisfy the demand of disaster areas. In order to find a better plan to achieve the multi-period disaster relief, in this paper, a multi-period emergency resource scheduling problem is solved using the multi-agent genetic algorithm (MAGA) considering the uncertainty of traffic. The experimental results show that multi-agent genetic algorithm is more effective than genetic algorithm (GA) for this problem and it has better convergence.
不确定交通网络中多周期应急资源调度问题的多智能体遗传算法
随着滑坡、地震等大型灾害的频繁发生,及时有效的应急资源调度变得越来越重要。许多灾害需要多期救援来满足灾区的需求。为了找到更好的方案来实现多时段的灾害救援,本文在考虑交通不确定性的情况下,采用多智能体遗传算法(MAGA)求解多时段的应急资源调度问题。实验结果表明,多智能体遗传算法比遗传算法(GA)更有效,具有更好的收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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