A new proactive-reactive approach to hedge against uncertain processing times and unexpected machine failures in the two-machine flow shop scheduling problems
In this paper, a proactive-reactive approach has been considered for achieving stable and robust schedules despite uncertain processing times and unexpected machine failures in a two-machine flow shop system. In the literature, Surrogate Measures (SMs) have been developed for achieving stable and robust solutions against the occurrence of stochastic disruptions. These measures proactively provide an approximation of the real conditions of the system in the event of a disruption. Because of the discrepancies of these measures with their real values, a dierent approach is developed in this paper in two-step structure. First, an initial robust schedule is produced and then, based on a multi-component measure, an appropriate reaction is adopted against unexpected machine failures. Computational results indicate that this method produces better solutions compared to the other two classical scheduling approaches considering their eectiveness and performance.
Rahmani, D. (2017). A new proactive-reactive approach to hedge against uncertain processing times and unexpected machine failures in the two-machine flow shop scheduling problems. Scientia Iranica, 24(3), 1571-1584. doi: 10.24200/sci.2017.4136
MLA
D. Rahmani. "A new proactive-reactive approach to hedge against uncertain processing times and unexpected machine failures in the two-machine flow shop scheduling problems". Scientia Iranica, 24, 3, 2017, 1571-1584. doi: 10.24200/sci.2017.4136
HARVARD
Rahmani, D. (2017). 'A new proactive-reactive approach to hedge against uncertain processing times and unexpected machine failures in the two-machine flow shop scheduling problems', Scientia Iranica, 24(3), pp. 1571-1584. doi: 10.24200/sci.2017.4136
VANCOUVER
Rahmani, D. A new proactive-reactive approach to hedge against uncertain processing times and unexpected machine failures in the two-machine flow shop scheduling problems. Scientia Iranica, 2017; 24(3): 1571-1584. doi: 10.24200/sci.2017.4136