Optimization and Engineering

, Volume 9, Issue 2, pp 143–160 | Cite as

Spent potliner treatment process optimization using a MADS algorithm

  • Charles Audet
  • Vincent Béchard
  • Jamal Chaouki


In this paper, the general problem of chemical process optimization defined by a computer simulation is formulated. It is generally a nonlinear, non-convex, non-differentiable optimization problem over a disconnected set. A brief overview of popular optimization methods from the chemical engineering literature is presented. The recent mesh adaptive direct search (MADS) algorithm is detailed. It is a direct search algorithm, so it uses only function values and does not compute or approximate derivatives. This is useful when the functions are noisy, costly or undefined at some points, or when derivatives are unavailable or unusable. In this work, the MADS algorithm is used to optimize a spent potliners (toxic wastes from aluminum production) treatment process. In comparison with the best previously known objective function value, a 37% reduction is obtained even if the model failed to return a value 43% of the time.


Simulation optimization Mesh adaptive direct search (MADS) algorithm Non-smooth optimization Spent potliners treatment 


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Charles Audet
    • 1
  • Vincent Béchard
    • 2
  • Jamal Chaouki
    • 2
  1. 1.GERAD and Department of Mathematics and Industrial EngineeringÉcole Polytechnique de MontréalMontréalCanada
  2. 2.Department of Chemical EngineeringÉcole Polytechnique de MontréalMontréalCanada

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