Cloud theory-based simulated annealing approach for scheduling in the two-stage assembly flowshop

In this paper we consider the two-stage assembly flowshop problems where we have m machines in the first stage and an assembly machine in the second stage. We aim to minimize a weighted sum of makespan and mean completion time as the objective for n available jobs. The problem is NP-hard, therefore we proposed the cloud theory-based simulated annealing algorithm (CSA) to solve it. In previous literature Allahverdi and Al-Anzi [5] showed that simulated annealing (SA) is an appropriate heuristic to solve this problem, so we have compared CSA and SA in this study. The computational results reveal that CSA performs better. In addition computational time has been decreased for the CSA algorithm towards the SA.