Advanced control strategies for smart windows (SW) are discussed in this paper. Since smart windows are used both to reduce energy consumption and to improve thermal and visual comfort@ the optimal solar flux passing throught the window is the result of a complex trade-off between daylighting and heat flow balance. A typical office building zone is modeled in TRNSYS with an integrated electrochromic smart window. Two types of advanced SW controllers@ i.e. (i) a genetic algorithm based controller and (ii) a model predictive control based controller@ are studied and compared to a base case scenario. The advanced controllers evaluate the hour-by-hour state of the smart window required to minimize the overall energy consumption (heating@ cooling@ lighting) while respecting constraints related to thermal and visual comfort. Results have shown that the two controllers@ while presenting different control strategies@ offer very similar and promising results in terms of energy savings and peak load reductions. Finally@ opportunities resulting from the present work are discussed.