Three-dimensional packing problems are important optimization problems with practical applications in various fields including manufacturing, logistics, and transportation. In this study, we focus on optimizing a multi-objective three-dimensional robotic packing problem. Our purpose is to simultaneously minimize both the processing time of the robot and the container's volume for a single packing task. To encode the packing solutions, we use the sequence-triple representation. Then, we calculate the robot processing time for each packing solution using the Rapidly Exploring Random Trees algorithm. The Non-dominated Sorting Genetic Algorithm II is employed to tackle this optimization problem. To examine the usefulness of the proposed approach, we conduct experiments using a 6-DOF robot manipulator. The results of our experiments illustrate the proposed algorithm can obtain a set of Pareto solutions, and a trade-off relationship exists between the processing time and the volume of the container.