A dispatching algorithm for parallel machines with rework processes

This paper presents a parallel machine scheduling problem with rework probabilities, due-dates and sequence-dependent setup times. It is assumed that rework probability for each job on a machine can be given through historical data acquisition. Since the problem is NP-hard in the strong sense, a heuristic algorithm is presented, which finds good solutions. The dispatching algorithm named MRPD (minimum rework probability with due-dates) is proposed in this paper focusing on the rework processes. The performance of MRPD is measured by the six diagnostic indicators: total tardiness, maximum lateness, mean flow-time, mean lateness, the number of reworks and the number of tardy jobs. A large number of test problems are randomly generated to evaluate the performance of the proposed algorithm. Computational results show that the proposed algorithm is significantly superior to existing dispatching algorithms for the test problems.