Vehicle configuration design with a packing genetic algorithm

3D packing problems occur in many applications. Exhaustive search methods cannot identify an optimum packing in reasonable time. To improve the search efficiency of such problems, a packing Genetic Algorithm (GA) with a new encoding method and packing GA operators is proposed. The method is applied to a vehicle configuration design problem, in which the goal is to maximise the vehicle survivability, maintainability and minimise vehicle rollover tendency by finding optimal positions of vehicle components. The packing GA is integrated with a Multi-Objective Genetic Algorithm (MOGA) to search for a non-dominated front, which offers trade-off solutions to the designer.

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