Prof Emma Hart E.Hart@napier.ac.uk
Professor
Prof Emma Hart E.Hart@napier.ac.uk
Professor
Peter Ross
Wolfgang Banzhaf
Editor
Jason M Daida
Editor
A E Eiben
Editor
Max H Garzon
Editor
Vasant Honavar
Editor
Mark Jakiela
Editor
Robert E Smith
Editor
This paper describes the application of an artificial immune system, (AIS), model to a scheduling application, in which sudden changes in the scheduling environment require the rapid production of new schedules. The model operates in two phases: In the first phase of the system, the immune system analogy, in conjunction with a genetic algorithm, (GA), is used to detect common patterns amongst scheduling sequences frequently used by a factory. In phase II, some of the combinatoric features of the natural immune system are modelled in order to use the detected patterns to produce new schedules, either from scratch or starting from a partially completed schedule. The results are compared to those calculated using an exhaustive search procedure to generate patterns. The AIS/GA analogy appears to be extremely promising, in that schedules corresponding to situations previously encountered can easily be reconstructed, and also in that the patterns are shown to incorporate sufficient information to potentially construct schedules for previously unencountered situations.
Hart, E., & Ross, P. (1999, July). An immune system approach to scheduling in changing environments. Presented at Genetic and Evolutionary Computation Conference ; GECCO-99
Conference Name | Genetic and Evolutionary Computation Conference ; GECCO-99 |
---|---|
Start Date | Jul 13, 1999 |
End Date | Jul 17, 1999 |
Publication Date | 1999 |
Deposit Date | Sep 6, 2010 |
Peer Reviewed | Peer Reviewed |
Pages | 1559-1566 |
Book Title | GECCO-99 : proceedings of the genetic and evolutionary computation conference. Volume 2 |
ISBN | 1558606114 |
Keywords | artificial immune system; scheduling; genetic algorithm; |
Public URL | http://researchrepository.napier.ac.uk/id/eprint/3173 |
Additional Information | A joint meeting of the Eighth International Conference on Genetic Algorithms (ICGA-99) and the Fourth Annual Genetic Programming Conference (GP-99). |
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