Paper Info
Title
A jigsaw puzzle inspired algorithm for solving large-scale no-wait flow shop scheduling problems
Abstract
The no-wait flow shop scheduling problem (NWFSP), as a typical NP-hard problem, has important ramifications in the modern industry. In this paper, a jigsaw puzzle inspired heuristic (JPA) is proposed for solving NWFSP with the objective of minimizing makespan. The core idea behind JPA is to find the best match for each job until all the jobs are scheduled in the set of process. In JPA, a waiting time matrix is constructed to measure the gap between two jobs. Then, a matching matrix based on the waiting time matrix is obtained. Finally, the optimal scheduling sequence is built by using the matching matrix. Experimental results on large-scale benchmark instances show that JPA is superior to the state-of-the-art heuristics.
Year
DOI
Venue
2020
10.1007/s10489-019-01497-2
Applied Intelligence
Keywords
Field
DocType
No-wait flow shop scheduling, Makespan, Heuristic algorithm, Jigsaw puzzle
Heuristic,Mathematical optimization,Job shop scheduling,Matrix (mathematics),Computer science,Scheduling (computing),Heuristic (computer science),Flow shop scheduling,Heuristics,Artificial intelligence,Jigsaw,Machine learning
Journal
Volume
Issue
ISSN
50
1
0924-669X
Citations 
PageRank 
References 
1
0.35
0
Authors
7
Name
Order
Citations
PageRank
Fuqing Zhao112922.63
Xuan He221.37
Yi Zhang340077.93
Wenchang Lei410.35
Weimin Ma542726.76
Chuck Zhang611715.72
Houbin Song7122.19