Matheuristics pp 231-244 | Cite as

A Good Recipe for Solving MINLPs

  • Leo Liberti
  • Giacomo Nannicini
  • Nenad Mladenović
Part of the Annals of Information Systems book series (AOIS, volume 10)


Finding good (or even just feasible) solutions for Mixed-Integer Nonlinear Programming problems independently of the specific problem structure is a very hard but practically useful task, especially when the objective and/or the constraints are nonconvex. We present a general-purpose heuristic based on Variable Neighbourhood Search, Local Bran-ching, Sequential Quadratic Programming and Branch-and-Bound. We test the proposed approach on the MINLPLib, discussing optimality, reliability and speed.


Sequential Quadratic Programming Variable Neighbourhood Mixed Integer Nonlinear Program Sequential Quadratic Programming Method Sequential Quadratic Programming Algorithm 


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We are very grateful to Prof. Tapio Westerlund for carefully checking all the computational results and informing us of some misprints on the MINLPLib website.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Leo Liberti
    • 1
  • Giacomo Nannicini
    • 1
  • Nenad Mladenović
    • 2
    • 3
  1. 1.LIX, École PolytechniquePalaiseauFrance
  2. 2.Brunel UniversityLondonUK
  3. 3.Institute of Mathematics, Academy of SciencesBelgradeSerbia

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