Abstract

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.

Details

Title
Improved firefly algorithm with courtship learning for unrelated parallel machine scheduling problem with sequence-dependent setup times
Author
Huang, Xingwang 1 ; Chen Lingqing 2 ; Zhang, Yuxin 2 ; Su Shubin 2 ; Lin Yangbin 2 ; Cao Xuhui 2   VIAFID ORCID Logo 

1  College of Computer Engineering, Jimei University, 185 Yinjiang Rd., Jimei District, Xiamen, China (GRID:grid.411902.f) (ISNI:0000 0001 0643 6866); Spatial Intelligence Lab, Jimei University, 185 Yinjiang Rd., Jimei District, Xiamen, China (GRID:grid.411902.f) (ISNI:0000 0001 0643 6866) 
2  College of Computer Engineering, Jimei University, 185 Yinjiang Rd., Jimei District, Xiamen, China (GRID:grid.411902.f) (ISNI:0000 0001 0643 6866) 
Publication year
2022
Publication date
Dec 2022
Publisher
Springer Nature B.V.
e-ISSN
2192113X
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1186/s13677-022-00282-w
ProQuest document ID
2638312954
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.