Pipe routing is the technique of developing collision-free routes for pipes between two locations in an environment scattered with obstacles. In the past, research has been primarily focused on the use of deterministic optimization techniques to derive the optimal route. Computational efficiency of deterministic techniques is low for highly nonlinear and sometimes discontinuous problems like pipe routing. Besides, due to limitations in the representation of 3D geometry, the shape obstacles have been restricted to primitives. In this research, a novel approach to overcome these limitations is presented. A nondeterministic optimization approach based on genetic algorithms (GAs) is proposed to generate pipe routing solution sets with a good searching efficiency. Representation of the objects and pipes in the tessellated format offers huge benefits in computation as well as usage. The versatility of the current approach and its ability to accommodate and efficiently solve problems involving 3D freeform obstacles is demonstrated.
ASJC Scopus subject areas
- Computer Science(all)