.png){kind=icon}
.png){kind=icon}
Return
Improved firefly algorithm with courtship learning for unrelated parallel machine scheduling problem with sequence-dependent setup times
.png){kind=icon}
OA
AI
DOI：10.1186/s13677-022-00282-w.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En
The Unrelated Parallel Machines Scheduling Problem (UPMSP) with sequence-dependent setup times has been widely applied to cloud computing, edge computing and so on. When the setup times are ignored, UPMSP will be a NP problem. Moreover, when considering the sequence related setup times, UPMSP is difficult to solve, and this situation will be more serious in the case of high-dimensional. This work firstly select the maximum completion time as the optimization objective, which establishes a mathematical model of UPMSP with sequence-dependent setup times. In addition, an improved firefly algorithm with courtship learning is proposed. Finally, in order to provide an approximate solution in an acceptable time, the proposed algorithm is applied to solve the UPMSP with sequence-dependent setup times. The experimental results show that the proposed algorithm has competitive performance when dealing with UPMSP with sequence-dependent setup times.
Keywords:
Firefly algorithm
Courtship learning
Unrelated parallel machines scheduling
Makespan
Sequence-dependent setup times
Journal
J
IF:
4.3
Papers:
738
Citations:
2.2K