In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II (NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy (E), peak crushing force (Fmax) and mass of the structure (W) as three conflicting objective functions. In the multi-objective optimization problem (MOP), E and Fmax are defined by polynomial models extracted using the software GEvoM based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point (NIP) method and technique for ordering preferences by similarity to ideal solution (TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method.
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