Operational research and machine learning: An engineering course

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Resumen

In this work, we integrate computational techniques based on machine learning (ML) and computational intelligence (IC) to conventional methodologies used in the Operational Research (OR) degree course for Engineers. That synergy between those techniques and methods allows students to deal with complex problems. The main contribution of this paper is to present a different proposal for OR courses using the synergy between mathematical models employing computer simulations, IC and different hybrid models.
Idioma originalInglés
Título de la publicación alojadaEDUNINE 2019 - 3rd IEEE World Engineering Education Conference
Subtítulo de la publicación alojadaModern Educational Paradigms for Computer and Engineering Career, Proceedings
EditoresClaudio Da Rocha Brito, Melany M. Ciampi
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)978-1-7281-1666-2
DOI
EstadoPublicada - 1 mar. 2019
EventoEDUNINE 2019 - 3rd IEEE World Engineering Education Conference: Modern Educational Paradigms for Computer and Engineering Career, Proceedings -
Duración: 1 mar. 2019 → …

Conferencia

ConferenciaEDUNINE 2019 - 3rd IEEE World Engineering Education Conference: Modern Educational Paradigms for Computer and Engineering Career, Proceedings
Período1/03/19 → …

Nota bibliográfica

Funding Information:
We would like to thank Masayuki Umemura, Jun Fukue, Shin Mineshige, Keiichi Wada, Toru Yamada, Hideaki Mouri, and Neil Trentham for useful discussion and comments. This work was financially supported in part by Grant-in-Aids for the Scientific Research (No. 0704405) of the Japanese Ministry of Education, Culture, Sport, and Science.

Publisher Copyright:
© 2019 IEEE.

Palabras clave

  • hybrid models
  • machine learning
  • operational research
  • optimization

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