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An overview of MINLP algorithms and their implementation in Muriqui Optimizer

  • S.I.: CLAIO 2016
  • Published:
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Abstract

We present an overview of the main algorithms in the literature for convex mixed integer nonlinear programming and discuss aspects of their implementation in a new open source computational package called Muriqui Optimizer. We provide extensive computational results comparing the implementations of all approaches considered on a set of 343 benchmark test problems. Finally, we present to the technical and scientific community the new software Muriqui Optimizer.

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Acknowledgements

Marcia Fampa was partially supported by CNPq (National Council for Scientific and Technological Development) Grant 303898/2016-0, as Fernanda Raupp was partially supported by CNPq Grant 307679/2016-0. The authors are grateful to the anonymous referees for their helpful insight.

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Authors and Affiliations

  1. College of Computer Science, Federal University of Uberlandia, Uberlândia, Brazil

    Wendel Melo

  2. Institute of Mathematics and COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

    Marcia Fampa

  3. National Laboratory for Scientific Computing (LNCC) of the Ministry of Science, Technology and Innovation, Petrópolis, Brazil

    Fernanda Raupp

Authors
  1. Wendel Melo
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  2. Marcia Fampa
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  3. Fernanda Raupp
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Correspondence to Wendel Melo.

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Melo, W., Fampa, M. & Raupp, F. An overview of MINLP algorithms and their implementation in Muriqui Optimizer. Ann Oper Res 286, 217–241 (2020). https://doi.org/10.1007/s10479-018-2872-5

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  • DOI: https://doi.org/10.1007/s10479-018-2872-5

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