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.
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