Abstract
This paper presents a probabilistic model of budget allocation for improving the efficiency of the transportation network in pre and post-disaster situations. We examine two problems to enhance the network performance by: (i) improving the overall travel time of the transportation network in the day-to-day conditions, and (ii) decreasing fatalities of the disaster by stabilizing the infrastructure to improve the network resiliency. The approach is based on a Stackelberg game, where the policymaker (i.e., the leader) allocates an available budget for either expanding or stabilizing the links of the transportation network. The two follower problems maximize the network performance in pre and post-disaster conditions. The proposed algorithm uses the Particle Swarm Optimization method for optimizing the leader's objective which is to minimize the overall societal costs. We conduct multiple simulations on small and big test cases to verify the accuracy and efficiency of the proposed method. The results show a reduction of 10% and 28% in the imposed cost to the society for small and big networks compared to non-integrated method, respectively.
Published Version
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