Name
Title | ||
|---|---|---|
A hybrid dual-population genetic algorithm for the single machine maximum lateness problem |
Abstract | ||
|---|---|---|
We consider the problem of scheduling a number of jobs, each job having a release time, a processing time and a due date, on a single machine with the objective of minimizing the maximum lateness. We developed a hybrid dual-population genetic algorithm and compared its performance with alternative methods on a new diverse data set. Extensions from a single to a dual population by taking problem specific characteristics into account can be seen as a stimulator to add diversity in the search process, which has a positive influence on the important balance between intensification and diversification. Based on a comprehensive literature study on genetic algorithms in single machine scheduling, a fair comparison of genetic operators was made. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-20364-0_2 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
processing time,release time,hybrid dual-population genetic algorithm,comprehensive literature study,genetic operator,genetic algorithm,single machine,alternative method,single machine scheduling,single machine maximum lateness,problem specific characteristic,branch,population genetics | Population,Single-machine scheduling,Mathematical optimization,Scheduling (computing),Computer science,Diversification (marketing strategy),Operator (computer programming),Population-based incremental learning,Genetic algorithm | Conference |
Volume | ISSN | Citations |
6622 | 0302-9743 | 5 |
PageRank | References | Authors |
0.44 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Veronique Sels | 1 | 39 | 2.96 |
| M Vanhoucke | 2 | 919 | 55.85 |