Standalone street lighting as a preferred application for road lighting faces two important issues: supply performance and energy cost. According to past research, optimization of hybrid renewable energy system (HRES) in street light supply seems the best known approach to deal with these issues. However, the complex design of street light supply with non-linearity of power units and uncertainty of load pattern makes optimization a challenge. This study employs genetic algorithm (GA) optimization to deal with these complex and uncertain systems. In order to optimize streetlight supply, it takes into account the energy cost for a single-objective problem and both the energy cost and supply performance for a multi-objective problem. This study also integrates traffic-based lighting control to overcome the power consumption issue in the load side affecting the optimum design of the streetlight supply. The system including real weather data, real traffic conditions and optimization algorithm are simulated using MATLAB. Based on the results, the proposed method reduces the power consumption by around 47% for a one-year simulation study. Moreover, the optimal design of streetlight supply potentially minimizes power loss by approximately 39% and energy cost by about 29%.