A Lagrangian Relaxation Approach for Unit Commitment with Stochastic Disruption Management

We investigate the unit commitment problem of how to recover the schedule when a disruption with stochastic duration occurs. The optimization problem is formulated to be a large-scale mixed integer programming (MIP). The solution approach is based on Lagrangian relaxation and dynamic programming. The computational results show that our algorithm performs well and the solutions found in a reasonable time are within 0.1% of the optimums averagely.