The objective of all manufacturers is to produce high-quality products at reasonable prices. In high-volume mass production systems, optimizing the operation sequence (OS) not only reduces product cost but also increases production efficiency. An optimal OS can be achieved by trimming unnecessary segments of motion from the tool path (TP), which reduces production time. Currently, a computer numerical control (CNC) program can be generated for a given TP by the number of automatic programing packages (APPs) that are currently available. However, TP optimization is not included in most APPs. In this study, we propose genetic algorithms (GAs) to determine the optimal OS for the TP pass through a set of operations located asymmetrically in multiple levels and using one or more cutting tools. Then, the CNC program of the TP will be generated. The traveling salesman problem is introduced to define the OS problem. A GA based on the TSP formulation can determine the OS that achieves the shortest TP. The incorporation of a GA and TSP can be integrated into the APP for TP optimization before creating CNC programs.