Name
Abstract | ||
|---|---|---|
We consider a job shop problem with uncertain processing times modelled as triangular fuzzy numbers and propose a methodology to study solution robustness with respect to different perturbations in the durations. This methodology is applied to obtain experimental results for several problem instances, using a hybrid genetic algorithm that minimises the expected makespan. We conclude that taking into account the uncertainty information provided by fuzzy numbers produces proactive solutions, coping well with posterior changes in processing times. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-88309-8_4 | IBERAMIA |
Keywords | Field | DocType |
expected makespan,fuzzy number,posterior change,problem instance,triangular fuzzy number,different perturbation,hybrid genetic algorithm,schedule robustness,uncertain processing time,job shop,job shop problem | Mathematical optimization,Job shop scheduling,Computer science,Job shop,Flow shop scheduling,Robustness (computer science),Fuzzy number,Possibility distribution,Genetic algorithm | Conference |
Volume | ISSN | Citations |
5290 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Inés González-Rodríguez | 1 | 115 | 10.73 |
| Jorge Puente | 2 | 171 | 13.16 |
| Ramiro Varela | 3 | 301 | 29.96 |
| Camino R. Vela | 4 | 346 | 31.00 |