The 3D bin packing problem (3D-BPP) is one of the most challenging problems in the lo- gistics industry. The objective of this Thesis is to explore the optimization of the 3D-BPP within a logistics context, focusing on several critical goals: maximizing space utilization, minimizing object fragility, and ensuring balanced weight distribution. We present a novel GRASP (Greedy Randomized Adaptive Search Procedure) algorithm tailored to address the 3D-BPP. The proposed method integrates several novel elements and builds upon the contributions of key researchers in the field. It also identifies potential improvements to the algorithm and suggests directions for future research to advance the state-of-the-art in solving the 3DPPP.