This paper deals with the robust safety design optimization of a rail vehicle system moving in short radius curved tracks. A combined multi-objective imperialist competitive algorithm and Monte Carlo method is developed and used for the robust multi-objective optimization of the rail vehicle system. This robust optimization of rail vehicle safety considers simultaneously the derailment angle and its standard deviation where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the rail vehicle safety to the design parameters uncertainties compared to the determinist one and to the literature results.

Accepted:

Published online:

Mohamed Nejlaoui ^{1};
Ajmi Houidi ^{2};
Zouhaier Affi ^{1};
Lotfi Romdhane ^{3}

@article{CRMECA_2017__345_10_712_0, author = {Mohamed Nejlaoui and Ajmi Houidi and Zouhaier Affi and Lotfi Romdhane}, title = {A hybrid multi-objective imperialist competitive algorithm and {Monte} {Carlo} method for robust safety design of a rail vehicle}, journal = {Comptes Rendus. M\'ecanique}, pages = {712--723}, publisher = {Elsevier}, volume = {345}, number = {10}, year = {2017}, doi = {10.1016/j.crme.2017.05.014}, language = {en}, }

TY - JOUR AU - Mohamed Nejlaoui AU - Ajmi Houidi AU - Zouhaier Affi AU - Lotfi Romdhane TI - A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle JO - Comptes Rendus. Mécanique PY - 2017 SP - 712 EP - 723 VL - 345 IS - 10 PB - Elsevier DO - 10.1016/j.crme.2017.05.014 LA - en ID - CRMECA_2017__345_10_712_0 ER -

%0 Journal Article %A Mohamed Nejlaoui %A Ajmi Houidi %A Zouhaier Affi %A Lotfi Romdhane %T A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle %J Comptes Rendus. Mécanique %D 2017 %P 712-723 %V 345 %N 10 %I Elsevier %R 10.1016/j.crme.2017.05.014 %G en %F CRMECA_2017__345_10_712_0

Mohamed Nejlaoui; Ajmi Houidi; Zouhaier Affi; Lotfi Romdhane. A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle. Comptes Rendus. Mécanique, Volume 345 (2017) no. 10, pp. 712-723. doi : 10.1016/j.crme.2017.05.014. https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.1016/j.crme.2017.05.014/

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