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.
|Título de la publicación alojada||EDUNINE 2019 - 3rd IEEE World Engineering Education Conference|
|Subtítulo de la publicación alojada||Modern Educational Paradigms for Computer and Engineering Career, Proceedings|
|Editores||Claudio Da Rocha Brito, Melany M. Ciampi|
|Editorial||Institute of Electrical and Electronics Engineers Inc.|
|ISBN (versión digital)||978-1-7281-1666-2|
|Estado||Publicada - 1 mar. 2019|
|Evento||EDUNINE 2019 - 3rd IEEE World Engineering Education Conference: Modern Educational Paradigms for Computer and Engineering Career, Proceedings - |
Duración: 1 mar. 2019 → …
|Conferencia||EDUNINE 2019 - 3rd IEEE World Engineering Education Conference: Modern Educational Paradigms for Computer and Engineering Career, Proceedings|
|Período||1/03/19 → …|
Nota bibliográficaFunding 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.
© 2019 IEEE.
- hybrid models
- machine learning
- operational research