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

Yawen Zhou, Jing Liu

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.