Name
Abstract | ||
|---|---|---|
In this paper, we consider a dynamic job shop scheduling problem (DJSSP) with job release dates. In such a problem, jobs arrive over time and are unknown in advance and they can not be scheduled before their arrivals. We apply gene expression programming (GEP), a new search technique based on evolutionary principle, on the scheduling problem to automatically construct efficient scheduling rules (SRs), which can generate high-quality schedules for the problem. A novel encoding scheme is proposed which prevents the length of chromosomes from increasing dramatically with the increase of the size of scheduling problems. And a new decoding scheme is also proposed which transfers a GEP chromosome into a schedule for each problem instance. The proposed GEP-based method is valuated for its solution quality. According to computational experiment results, the method is proved to be able to construct effective SRs for DJSSP with job release dates. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CSCWD.2011.5960088 | CSCWD |
Keywords | Field | DocType |
dynamic scheduling,encoding scheme,release date,evolutionary principle,encoding,search problems,search technique,gep chromosome,job shop scheduling,dynamic job shop scheduling problem,genetic algorithms,dynamic job shop scheduling,scheduling rule,scheduling rules,job release dates,gene expression programming,decoding,scheduling problem,computer experiment,schedules | Mathematical optimization,Multiprocessor scheduling,Job shop scheduling,Fair-share scheduling,Scheduling (computing),Computer science,Flow shop scheduling,Schedule,Rate-monotonic scheduling,Dynamic priority scheduling,Distributed computing | Conference |
Volume | Issue | ISBN |
null | null | 978-1-4577-0386-7 |
Citations | PageRank | References |
5 | 0.42 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Nie | 1 | 42 | 3.58 |
| Liang Gao | 2 | 176 | 21.99 |
| Peigen Li | 3 | 389 | 28.81 |
| Liping Zhang | 4 | 15 | 7.51 |