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/
[1] Multiobjective robust design optimization of rail vehicle moving in short radius curved tracks based on the safety and comfort criteria, Simul. Model. Pract. Th., Volume 30 (2013), pp. 21-34
[2] Optimization of curving performance of rail vehicles, Veh. Syst. Dyn., Volume 43 (2005), pp. 895-923
[3] Assessment of running safety of railway vehicles using multibody dynamics, Int. J. Precis. Eng. Man., Volume 11 (2010), pp. 315-320
[4] Bond graph modeling of a railway truck on curved track, Simul. Model. Pract. Th., Volume 17 (2009), pp. 22-34
[5] Application of Markov modelling and Monte Carlo simulation technique in failure probability estimation—a consideration of corrosion defects of internally corroded pipelines, Eng. Fail. Anal., Volume 68 (2016), pp. 159-171
[6] Monte Carlo uncertainty simulation of surface emissivity at ambient temperature obtained by dual spectral infrared radiometry, Infrared Phys. Technol., Volume 67 (2014), pp. 131-137
[7] Using Monte-Carlo approach for analysis of quantitative and qualitative operation of reservoirs system with regard to the inflow uncertainty, J. Afr. Earth Sci., Volume 105 (2015), pp. 1-16
[8] Robust optimization using hybrid differential evolution and sequential quadratic programming, Eng. Optim., Volume 47 (2015) no. 1, pp. 87-106
[9] Multi-objective robust optimization of unidirectional carbon/glass fibre reinforced hybrid composites under flexural loading, Compos. Struct., Volume 138 (2016), pp. 264-275
[10] Robust optimization of the non-linear behavior of a vibrating system, Eur. J. Mech. A, Solids, Volume 28 (2009), pp. 141-154
[11] Analytical modeling of rail vehicle safety and comfort in short radius curved tracks, C. R. Mecanique, Volume 337 (2009), pp. 303-311
[12] Numerical Optimization, Springer-Verlag, 1999 (ISBN: 0-387-98793-2)
[13] An improved imperialist competitive algorithm for multi-objective optimization, Eng. Optim., Volume 48 (2016) no. 11, pp. 1823-1844
[14] Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition, Singapore (2007), pp. 4661-4667
[15] MOICA: a novel multi-objective approach based on imperialist competitive algorithm, Appl. Math. Comput., Volume 219 (2013), pp. 8829-8841
[16] Water cycle algorithm for solving constrained multi-objective optimization problems, Appl. Soft Comput., Volume 27 (2015), pp. 279-298
[17] Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems, Appl. Intell., Volume 46 (2017), p. 79 | DOI
Cited by Sources:
Comments - Policy