Flowshop scheduling with machine deterioration based on job sequences

This paper addresses the two-machine permutation flowshop problem with deterioration. The objectives are minimizing the makespan and the average tardiness. Jobs have a baseline process time in each machine and have a due date. The actual time to process a job depends on the machine performance level at the start of each job, which is a function of the previously processed jobs and their wear/deterioration effect on the machine. The article proposes multiple heuristics and a comprehensive set of experiments. The results indicate that as a group, the heuristics generate solutions that are very close to the optimal for both criteria. Furthermore, no heuristic approach is dominant for all experimental conditions, thus heuristic selection to solve practical problems should be based on the specific problem characteristics.

Discrete imperialist competitive algorithm for the resource-constrained hybrid flowshop problem with energy consumption

The resource-constrained hybrid flowshop problem (RCHFS) has been investigated thoroughly in recent years. However, the practical case that considers both resource-constrained and energy consumption still has rare research. To address this issue, a discrete imperialist competitive algorithm (DICA) was proposed to minimize the makespan and energy consumption. In the proposed algorithm, first, each solution was represented by a two-dimensional vector, where one vector represented the scheduling sequence and another one showed the machine assignment. Then, a decoding method considering the resource allocation was designed. Finally, we combined DICA and the simulated annealing algorithm (SA) to improve the performance of the proposed approach. Furthermore, we tested the proposed algorithm based on a randomly generated set of real shop scheduling system instances and compared with the existing heuristic algorithms. The results confirmed that the proposed algorithm can solve the RCHFS with high efficiency.