Title: Multi-surrogate-assisted metaheuristics for crashworthiness optimisation

Authors: Cho Mar Aye; Nantiwat Pholdee; Ali R. Yildiz; Sujin Bureerat; Sadiq M. Sait

Addresses: Sustainable Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, Thailand ' Sustainable Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, Thailand ' Department of Automotive Engineering, Bursa Uludag University, Bursa, 16059, Turkey ' Sustainable Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, Thailand ' Department of Computer Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia

Abstract: This work proposes a multi-surrogate-assisted optimisation and performance investigation of several newly developed metaheuristics (MHs) for the optimisation of vehicle crashworthiness. The optimisation problem for car crashworthiness is posed to find the shape and size of a crash box while the objective function is to maximise the total energy absorption subject to a mass constraint. Two main numerical experiments are conducted. Firstly, the performance of different surrogate models along with the proposed multi-surrogate model is investigated. Secondly, several MHs are applied to tackle the proposed crashworthiness optimisation problem by employing the best obtained surrogate model. The results reveal that the proposed multi-surrogate model is the best performer. Among the several MHs used in this study, sine cosine algorithm is the best algorithm for the proposed multi-surrogate model. Based on this study, the application of the proposed multi-surrogate model is better than using one particular traditional surrogate model, especially for constrained optimisation.

Keywords: surrogate-assisted optimisation; crash box design; evolutionary algorithm; constrained optimisation; meta-heuristics; crashworthiness optimisation; Kriging model.

DOI: 10.1504/IJVD.2019.109866

International Journal of Vehicle Design, 2019 Vol.80 No.2/3/4, pp.223 - 240

Received: 08 Aug 2019
Accepted: 09 Mar 2020
Published online: 28 Sep 2020 *

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