Artificial memory in production management
Abstract
The scheduling of parts in a production system is an NP-complete problem. To search an optimal solution is incompatible with the "real time" constraint. The usual procedures (clusters-job, introduction of constraints on the fabrication starting time, hierarchical schedulind) all contribute to vanish the combinatorial aspect of the problem. We propose to memorize some behaviour-classes and to use them in order to choose the management rule in relation with the aimed targets. A numerical example will describe this approach.