This paper presents an heuristic Genetic Algorithm for solving 3-Dimensional Single container packing optimization problem. The 3D container loading problem consists of ‘n’ number of boxes being to be packed in to a container of standard dimension in such a way to maximize the volume utilization and inturn profit. Furthermore, various practical constraints like box orientation, stack priority, container stability, etc also applied. Boxes to be packed are of various sizes and of heterogeneous shapes. In this research work, several heuristic improvements were proposed over Genetic Algorithm (GA) to solve the container loading problem that significantly improves the search efficiency and to load most of heterogeneous boxes into a container along with the optimal position of loaded boxes, box orientation and boxes to be loaded by satisfying practical constraints. In this module, both the guillotine and non-guillotine moves were allowed. In general, these heuristic GA solutions being substantially better and satisfactory than those obtained by applying heuristics to the bin packing directly.