Genetic algorithm optimizations of traffic signal timings have been shown to be effective, continually outperforming traditional optimization tools such as Synchro and TRANSYT-7F. However, their application has been limited to scholarly research and evaluations. Only one tool has matured to a commercial deployment: direct CorSim optimization, a feature of TRANSYT-7F. A genetic algorithm formulation, VisSim-based genetic algorithm optimization of signal timings (VISGAOST), is presented; it builds on the best of the recorded methods by extending their capabilities. It optimizes four basic signal timing parameters with VisSim microsimulation as an evaluation environment. The program brings new optimization features not available in the direct CorSim optimization, such as the optimization of phasing sequences, multiple coordinated systems and uncoordinated intersections, fully actuated isolated intersections, and multiple time periods. The formulation has two features that enhance and reduce computational time: optimization resumption and parallel computing. The program has been tested on two VisSim networks: a hypothetical grid network and a real-world arterial of actuatedcoordinated intersections in Park City, Utah. The results show that timing plans optimized by the genetic algorithm outperformed the best Synchro plans in both cases, reducing delay and stops by at least 5%.