ISSN:
1572-9338
Keywords:
intelligent decision support, learning, genetic algorithms, simulation, scheduling
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
,
Economics
Notes:
Abstract This paper considers the automated learning of strategies for real-time scheduling in dynamic factory floor environments. A simulation model of the shop floor provides continuous inputs to a genetic algorithm based learning system. Learning is used to update the knowledge bases of "intelligent" dispatchers in the floor shop setup. The performance of the learning system is compared with that of commonly used dispatching rules, and experimental results are presented for a two-stage flowline and for a more general jobshop environment.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1018989730961
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