Abstract
The paper addresses the integration of optimization in the automated design process of ascent assemblies. The goal is to automatically search for an optimal path connecting user defined inspection points while avoiding obstacles. As a first step towards full automation of the ascent assembly design, a discrete 2D model abstraction is considered. This establishes a combinatorial optimization problem, which is tackled by the use of two distinct strategies: a greedy heuristic and a genetic algorithm variant. Applying modeling approach and algorithms to multiple test cases, partly artificial and partly based on a manufactured crane, shows that the automated ascent assembly design tasks can successfully be enhanced with optimal path planning.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Eurogen 2017 Conference |
| Place of Publication | Madrid, Spain |
| Publisher | Technical University of Madrid |
| Number of pages | 8 |
| Publication status | Published - Sept 2017 |
Fields of science
- 101 Mathematics
- 101013 Mathematical logic
- 101024 Probability theory
- 102001 Artificial intelligence
- 102003 Image processing
- 102019 Machine learning
- 603109 Logic
- 202027 Mechatronics
JKU Focus areas
- Computation in Informatics and Mathematics
- Mechatronics and Information Processing
- Nano-, Bio- and Polymer-Systems: From Structure to Function