There is an increasing customer demand for adjustable chassis control features which enable adaption of the vehicle comfort and driving characteristics to the customer requirements. One of the most promising vehicle control systems which can be used to change the vehicle characteristics during the drive is the semi-active suspension system. This paper presents a Rule-Optimized Fuzzy Logic controller for semi-active suspension systems which can continuously adjust itself not only according to the road conditions but also to the driver requirements. The proposed controller offers three different control modes (Comfort, Normal and Sport) which can be switched by the driver during driving. The Comfort Mode minimizes the accelerations imposed on the driver and passengers by using a softer damping. On the other hand, the increased damping in Sport Mode provides better road holding capability, which is critical for sporty handling. The Normal Mode is adjusted to provide an overall balance between the vehicle ride comfort and road holding. The controller synthesis is performed by using an eleven degree of freedom full vehicle ride dynamics simulation model which is validated through laboratory tests performed on a hydraulic four-poster shaker. A unique optimization process is employed for obtaining the optimum Fuzzy Logic membership functions and the optimum rule-base of the proposed semi-active suspension controller. Discrete optimization is performed with Genetic Algorithm (GA) to find the global optima of the cost function which considers the ride comfort and road holding performance of the full vehicle. A comparison between the three control modes in terms of ride comfort and road holding is performed. The results show that, the proposed control modes provide three different vehicle characteristics to the driver. In addition to this, all three control modes are superior to the optimal passive suspension in terms of both ride comfort and road holding.