International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 57 - Number 16 |
Year of Publication: 2012 |
Authors: Mostafa Jannatipour, Babak Shirazi, Iraj Mahdavi |
10.5120/9196-3718 |
Mostafa Jannatipour, Babak Shirazi, Iraj Mahdavi . Fuzzy Simulation-based Genetic Algorithm for Just-in-Time Flow Shop Scheduling with Linear Deterioration Function. International Journal of Computer Applications. 57, 16 ( November 2012), 7-14. DOI=10.5120/9196-3718
In most of the flow shop scheduling problem studies, the processing times of jobs are considered constant and deterministic. These assumptions obviously suggest a significant gap between theory and real-world production problems. In this study, the problem of flow shop scheduling with linear job deterioration is addressed. This problem is investigated in an uncertain environment, and fuzzy theory is applied to describe this situation. The considered objective is minimizing the sum of fuzzy earliness and tardiness penalties. The problem which is known to be NP-hard is compatible with the concepts of just-in-Time (JIT) production. To solve this complex problem, a novel integrating optimization approach based on fuzzy simulation and genetic algorithm is proposed. A set of random test problems with different structures are presented to evaluate the performance of this approach. The computational results demonstrate effectiveness of the proposed approach.