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.
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Acknowledgements
The present work is supported by the Austrian Research Promotion Agency FFG through the funding program COMET in the K-Project “Advanced Engineering Design Automation (AEDA)” and by the Austrian Science Fund FWF under grant P29651-N32.
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Hellwig, M., Entner, D., Prante, T., Zăvoianu, AC., Schwarz, M., Fink, K. (2019). Optimization of Ascent Assembly Design Based on a Combinatorial Problem Representation. In: Andrés-Pérez, E., González, L., Periaux, J., Gauger, N., Quagliarella, D., Giannakoglou, K. (eds) Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems. Computational Methods in Applied Sciences, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-89890-2_19
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DOI: https://doi.org/10.1007/978-3-319-89890-2_19
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