||In this thesis, a combinatorial optimization model is developed to solve a newly emerged disruption scheduling problem in modern supply chain. When disruption occurs and paralyzes the production in one or several facilities, new high quality schedules need to be generated within a short decision period taking into consideration the cost of ordinary scheduling, cost fiom disruption and also cost from transportation. A special case of the problem is proved to be NP-hard in literature. A robust heuristic based on Tabu Search is developed to search for optimal or near optimal solutions. The components of the Tabu Search are specially designed and tested through extensive experimentation. The test problem is generated by an existing problem generation method from literature and also reasonable assumptions. The results show that our Tabu Search is superior to the acknowledged mathematical solver CPLEX in computation time for a wide range of problem size.