Abstract
In the automotive industry, the crashworthiness design of vehicles is of special importance. In this work, a multi-objective model for the vehicle design which minimizes three objectives, weight, acceleration characteristics, and toe-board intrusion, is considered, and a novel evolutionary algorithm based on decomposition and adaptive weight adjustment is designed to solve this problem. The experimental results reveal that the proposed algorithm works better than MOEA/D MOEA/D-AWA and NSGAII on this problem.
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Acknowledgements
This work was supported by National Natural Science Foundations of China (no. 61502290, no. 61401263, no. 61672334), China Postdoctoral Science Foundation (no. 2015M582606), Fundamental Research Funds for the Central Universities (no. GK201603094, no. GK201603002), and Natural Science Basic Research Plan in Shaanxi Province of China (no. 2016JQ6045, no. 2015JQ6228).
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Dai, C. (2020). A Decomposition-Based Evolutionary Algorithm with Adaptive Weight Adjustment for Vehicle Crashworthiness Problem. In: Pan, JS., Li, J., Tsai, PW., Jain, L. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 157. Springer, Singapore. https://doi.org/10.1007/978-981-13-9710-3_7
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DOI: https://doi.org/10.1007/978-981-13-9710-3_7
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