Name
Abstract | ||
|---|---|---|
Scheduling for semiconductor wafer fabrication is an important problem in actual production of manufacturing system , it is also one of the difficult problems of theory research. Genetic algorithm (GA) is one major object of computational intelligence. So, the study on genetic algorithm based semiconductor wafer fabrication scheduling has been paid much attention in the past few years due to its research value and increasing amount of importance in numerous applications. In this paper, we propose a GA based scheduler. In the GA scheduler, the chromosome represents a combination of scheduling policies, including lot released policies, machine selection rules, dispatch rules and batch rules. So, when the GA finishes its optimization process, an optimal scheduling policy is produced. From our experiment results, the GA will yield a more efficient solution than several other scheduler. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1543834.1544009 | GEC Summit |
Keywords | Field | DocType |
computational intelligence,optimal scheduling policy,theory research,semiconductor wafer fabrication scheduling,ga scheduler,genetic algorithm,research value,optimized scheduling,semiconductor wafer fabrication,actual production,batch rule,scheduling | Mathematical optimization,Fair-share scheduling,Computer science,Scheduling (computing),Scheduling (production processes),Two-level scheduling,Genetic algorithm scheduling,Rate-monotonic scheduling,Dynamic priority scheduling,Genetic algorithm | Conference |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cao Zhengcai | 1 | 42 | 16.38 |
| Fei Qiao | 2 | 1 | 3.10 |
| Qidi Wu | 3 | 426 | 44.87 |