Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 209-223 |
| Number of pages | 15 |
| Journal | Computers in Industry |
| Volume | 38 |
| Issue number | 3 |
| DOIs | |
| State | Published - Apr 1999 |
Funding
The authors wish to thank Matthew Wall at Massachusetts Institute of Technology for letting us use GALib (Genetic Algorithm Library) for this research. Thanks also go to Stefan Gottschalk at University of North Carolina, Chapel Hill for letting us use RAPID (rapid and accurate polygon interference detection) for this research. The support from NSF Faculty Early Career Award (DMI 9624363) is gratefully acknowledged. Mr. Sunand Sandurkar is a software engineer at Structural Dynamics Research in Cincinnati, OH. He received his Masters degree in Mechanical Engineering from Clemson University in 1997. He is the recipient of Hoechst Celanese Award for his outstanding performance during his masters program. He received his Bachelor of Engineering in Mechanical Engineering in 1995 from Vasavi College of Engineering in Hyderabad, India. Dr. Wei Chen became an Assistant Professor in the Mechanical Engineering Department at the University of Illinois at Chicago in August 1998. Before joining UIC, Dr. Chen was an assistant professor at the Clemson University and the co-director of the CREDO Lab (Clemson Research in Engineering Design and Optimization Lab). Her research goal is to advance the design theory, methods, and tools for those designs with a magnitude of complexity, in the context of globally competitive markets and the need to quickly respond to the change. Her current research involves issues such as robust design, multi-criteria decision making under risk and uncertainty, concept exploration of complex systems, distributed collaborative systems design, integrated product and process development, and computer aided design (CAD) and optimization. Dr. Chen received her PhD from the Georgia Institute of Technology in 1995. She is the recipient of the 1996 NSF Faculty Early Career Award and the 1998 ASME Pi Tau Sigma Gold Metal. Dr. Chen is a member of ASME, AIAA, and ASQC.
ASJC Scopus subject areas
- General Computer Science
- General Engineering