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

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Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12296))

Abstract

We 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.

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Authors and Affiliations

  1. Autodesk Research, 661 University Avenue, Toronto, ON, M5G 1M1, Canada

    Hyunmin Cheong, Mehran Ebrahimi & Adrian Butscher

  2. Augmenta Inc., 106 Front St E, Toronto, ON, M5A 1E1, Canada

    Chiara Piacentini

Authors
  1. Chiara Piacentini
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  2. Hyunmin Cheong
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  3. Mehran Ebrahimi
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  4. Adrian Butscher
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Corresponding authors

Correspondence to Chiara Piacentini or Hyunmin Cheong .

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Editors and Affiliations

  1. LAAS - CNRS, Toulouse, France

    Emmanuel Hebrard

  2. TU Wien, Vienna, Wien, Austria

    Nysret Musliu

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Piacentini, C., Cheong, H., Ebrahimi, M., Butscher, A. (2020). Multi-speed Gearbox Synthesis Using Global Search and Non-convex Optimization. In: Hebrard, E., Musliu, N. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2020. Lecture Notes in Computer Science(), vol 12296. Springer, Cham. https://doi.org/10.1007/978-3-030-58942-4_25

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  • DOI: https://doi.org/10.1007/978-3-030-58942-4_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58941-7

  • Online ISBN: 978-3-030-58942-4

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