The container relocation problem (CRP) for ports worldwide has been a highly significant research topic because of its contribution to the improvement of yard-running efficiency. It can be defined as a sequence that allows each container to be extracted with the least number of relocations when identical containers in a cluster have been stacked in a block. This study differs from previous research mainly in five aspects: (1) a two-level goal programming model for CRP is presented that can help in understanding of this problem and provide a solid theoretical ground for this research; (2) because of the NP time hardness of the CRP, heuristic rules are proposed to reduce hunting space by the way of dividing solution space; (3) an improved path optimum algorithm (I-POA) is proposed to reduce unfeasible solutions and find a high-quality solution for any three-dimensional case in a shorter running time; (4) the numerical experiments show that the algorithm proposed in this research achieves better performance than similar algorithms because of its higher levels of efficiency and more robust property; and (5) a general expression for the utilization level of the storage area and the number of relocations is proposed to check the reliability of the result by conducting a sensitivity analysis. Based on this research, the following conclusion can be obtained: I-POA possesses significant practical value in the improvement of intelligent resource scheduling standards of coastal container ports worldwide. \textcopyright 2018 Coastal Education and Research Foundation, Inc.