Searching. Please wait…
1582
37
171
29406
4423
2606
347
392
Abstract: In this paper we consider a variant of the open shop problem where task durations are allowed to be uncertain and where uncertainty is modelled using fuzzy numbers. Solutions to this problem are fuzzy schedules, which we argue should be seen as predictive schedules, thus establishing links with the concept of robustness and a measure thereof. We propose a particle swarm optimization (PSO) approach to minimise the schedule’s expected makespan, using priorities to represent particle position, as well as a decoding algorithm to generate schedules in a subset of possibly active ones. Our proposal is evaluated on a varied set of several benchmark problems. The experimental study includes a parametric analysis, results of the PSO compared with the state-of-the-art, and an empirical study of the robustness of taking into account uncertainty along the scheduling process.
Authorship: Palacios J., González-Rodríguez I., Vela C., Puente J.,
Fuente: Nat Comput (2014) 13:145–156
Publisher: Springer
Publication date: 31/01/2014
No. of pages: 12
Publication type: Article
DOI: 10.1007/s11047-014-9413-1
ISSN: 1567-7818,1572-9796
Spanish project: TIN2010-20976-C02-02 ; MTM2010-16051
Publication Url: http://link.springer.com/article/10.1007/s11047-014-9413-1
SCOPUS
Citations
Google Scholar
Metrics
Read publication
PALACIOS, JUAN JOSÉ
INES GONZALEZ RODRIGUEZ
VELA, CAMINO R.
PUENTE, JORGE
Back