1996 | ReviewPaper | Buchkapitel
Industrial plant pipe-route optimisation with genetic algorithms
verfasst von : Dae Gyu Kim, David Corne, Peter Ross
Erschienen in: Parallel Problem Solving from Nature — PPSN IV
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The pipe-route design problem for heavy industrial plant concerns minimising pipe material cost while satisfying constraints on required interconnections and obstacle avoidance. This process is invariably done by human experts, but modern stochastic iterative search techniques allow the opportunity to automate this process. This study explores the possibility of automated industrial pipe-route design on three test problems, using stochastic hillclimbing, simulated annealing, and genetic algorithms. The representation strategy is explained and discussed, and results are presented which show great promise for genetic algorithms in particular in this application area.