We propose a basic algorithm based on corner-occupied action for solving the 2D rectangular packing problem and a three-phase quasi-human global optimization algorithm. In the first phase, an initial configuration is generated. In the second phase, we optimize the priority levels of all rectangles by iteratively calling the local search sub-procedure and off-trap strategy sub-procedure. We adopt two neighborhood structures—swap and insertion instead of a single neighborhood structure in the local search sub-procedure to avoid some limitations. When the search encounters local optimal solutions, the off-trap strategy sub-procedure is called to jump out of the trap and guide the search into more promising areas. In the third phase, the beauty degree enumeration sub-procedure is called to optimize the selection of corner-occupied actions. We also derive two goodness degree theorems. Experiments on six sets of benchmark instances show that the proposed algorithm outperforms the best algorithms in the literature. For the two benchmark instances named zdf6 and zdf7, while the orientation of the rectangles is fixed the proposed algorithm can find better packing configurations than the best results reported in the literature up to now.