Name
Abstract | ||
|---|---|---|
In this paper we consider the single machine scheduling problem with truncated job-dependent learning effect. By the truncated job-dependent learning effect, we mean that the actual job processing time is a function which depends not only on the job-dependent learning effect (i.e., the learning in the production process of some jobs to be faster than that of others) but also on a control parameter. The objectives are to minimize the makespan, the total completion time, the total absolute deviation of completion time, the earliness, tardiness and common (slack) due-date penalty, respectively. Several polynomial time algorithms are proposed to optimally solve the problems with the above objective functions. ? 2012 Springer-Verlag Berlin Heidelberg. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s11590-012-0579-0 | Optimization Letters |
Keywords | Field | DocType |
learning effect,scheduling,single machine | Online machine learning,Mathematical optimization,Single-machine scheduling,Learning effect,Job shop scheduling,Tardiness,Computer science,Scheduling (production processes),Least slack time scheduling,Time complexity | Journal |
Volume | Issue | ISSN |
8 | 2 | 18624480 |
Citations | PageRank | References |
8 | 0.47 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xue-Ru Wang | 1 | 34 | 1.66 |
| Jibo Wang | 2 | 745 | 41.50 |
| Jian Jin | 3 | 103 | 11.73 |
| P Ji | 4 | 187 | 26.88 |