Multi-speed Gearbox Synthesis Using Global Search and Non-convex Optimization

AbstractWe consider the synthesis problem of a multi-speed gearbox, a mechanical system that receives an input speed and transmits it to an outlet through a series of connected gears, decreasing or increasing the speed according to predetermined transmission ratios. Here we formulate this as a bi-level optimization problem, where the inner problem involves non-convex optimization over continuous parameters of the components, and the outer task explores different configurations of the system. The outer problem is decomposed into sub-tasks and optimized by a variety of global search methods, namely simulated annealing, best-first search and estimation of distribution algorithm. Our experiments show that a three-stage decomposition coupled with a best-first search performs well on small-size problems, and it outmatches other techniques on larger problems when coupled with an estimation of distribution algorithm.

Download publication

Related Resources

See what’s new.



Team Size and Technology Fit: Participation, Awareness and Rapport in Distributed Teams

In this paper we investigate the effects that team size has on…



Neural Implicit Style-Net: synthesizing shapes in a preferred style exploiting self supervision

We introduce a novel approach to disentangle style from content in the…



Efficient Geometrically Exact Continuous Collision Detection

Continuous collision detection (CCD) between deforming triangle mesh…



Towards an Ontology for Generative Design of Mechanical Assemblies

In software-based generative design, a user specifies goals expressed…

Get in touch

Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.

Contact us