L. Geneste et B. Grabot, IMPLICIT VERSUS EXPLICIT KNOWLEDGE REPRESENTATION IN A JOB-SHOP SCHEDULING DECISION-SUPPORT SYSTEM, International journal of expert systems, 10(1), 1997, pp. 37-52
Citations number
17
Categorie Soggetti
Computer Sciences, Special Topics","Computer Science Artificial Intelligence
Job-shop scheduling is a key problem for many manufacturing firms. Due
to the underlying complexity, only heuristic methods can be used to s
olve this problem. The choice of a relevant scheduling strategy is bas
ed on the workshop and the manufacturing orders structure and on the o
bjectives of the workshop manager. We show in this paper how to take t
his information into account in order to select a relevant scheduling
strategy. A first approach is to represent the expertise on this domai
n explicitly. The managed information, such as the importance of an ob
jective according to the workshop manager, is often imprecise. Therefo
re a fuzzy inference system is described to support knowledge represen
tation. The second approach is to learn and to generalize the expertis
e implicitly from several typical situations thanks to neural networks
. Both approaches are described and compared with an industrial schedu
ling software.