Network recovery from large-scale failures considering the recovery resources and the upper limit of traffic demand

The network components will be seriously damaged after large-scale failures caused by natural disasters. The capacity of the network will be decreased and it may seriously affect users´ traffic. flow to repair the failed network components within the limited recovery resources and meet users´ traffic demand as much as possible is quite important. This paper mainly proposes the problem of selecting a subset of the failed components to repair after massive failures considering the recovery resources (workforce) and the upper limit of traffic demand so as to maximize to meet users´ traffic demand in the network. In this paper, we first formulate the problem using mixed integer programming (MIP). We then propose an effective heuristic algorithm called the Knapsack Problem of Shadow Price Recovery Heuristic Algorithm (KPSPR) to solve the iMIP model. Simulations are performed to study and compare the performance of the MIP and heuristic algorithms.