The growing demand for cleaner fuels and improved energy efficiency in the automotive industry has intensified research into turbocharged engines, particularly those based on the Atkinson cycle. This study focuses on the optimization and implementation of a turbocharged Atkinson-cycle gasoline engine to reduce fuel consumption and emissions under low-speed and part-load operating conditions. A genetic algorithm (GA)-based multi-variable optimization framework is developed to simultaneously optimize intake valve timing, valve lift, and exhaust gas recirculation (EGR) rates, thereby enhancing engine performance across a wide range of speed–load conditions. A validated one-dimensional GT-Power simulation model, integrated with MATLAB/Simulink, is employed to analyze the influence of valve timing strategies on mixture formation, combustion behavior, and emission characteristics. Both experimental testing and numerical simulations conducted on a 1.6 L turbocharged Atkinson-cycle engine corroborate the model predictions. The optimized configuration achieves a 2-3% reduction in brake-specific fuel consumption (BSFC), an 18% decrease in NO_x emissions, and up to a 2.5% reduction in CO₂ emissions. The findings demonstrate the significant potential of the Atkinson cycle to improve thermal efficiency under low-speed and part-load conditions, particularly when combined with advanced variable valve strategies and GA-based optimization techniques. Future research should explore the hybridization of Otto and Atkinson cycles, as well as the integration of advanced turbocharging technologies, to mitigate inherent power density limitations.