This study addresses a 3D Maximum Volume Packing Problem, aiming to maximize the volume of car components within the configuration space at the front of the vehicle. This scenario involves a fixed set of components, and the optimization goal is to maximize the volume of each component. Additionally, positional constraints must be satisfied to ensure the distribution of components aligns with practical assembly requirements. This study uses satisficing method to balance the multiply objectives where the minimum value of the normalized objective function is used as the optimization goal. The optimization process employs the Particle Swarm Optimization (PSO) algorithm. The paper also introduces an innovative "growth-based" configuration method, where each component gradually expands from a smaller volume. The initial positions and growth ratios of different components are treated as variables in the problem. Through the establishment of growth rules, the method can effectively prevent overlapping during the component configuration. Additionally, pareto solutions are obtained by setting different ideal values in the satisficing method. As a result, this method shows better performance than the basic PSO.
Shifan et al. (Wed,) studied this question.