Renewable energies are believed to play the key role in assuring a future of sustainable energy supply and low carbon emissions. Particularly, this thesis focus on wave energy, which is created by extracting the power stored in the waves of the oceans. In order for wave energy to become a commercialized form of energy, modular deployment of many wave energy converters (WECs) together will be required in the upcoming future. This design will thus allow to benefit, among others, from the modular construction, the shared electrical cables connections and moorings, the reduction in the power fluctuations and reduction of deployment and maintenance costs. When it comes to arrays, the complexity of the design process increase enormously compared with the single WEC, given the mutual influence of most of the design parameters (i.e. hydrodynamic and electrical interactions, dimensions, geometrical layout, wave climate etc.). Uppsala University has developed and tested WECs since 2001, with the first offshore deployment held in 2006. The device is classified as a point absorber and consists in a linear electric generator located on the seabed, driven in the vertical direction by the motion of a floating buoy at the surface. Nowadays, one of the difficulties of the sector is that the cost of electricity is still too high and not competitive, due to high capital and operational costs and low survivability. Therefore, one step to try to reduce these costs is the development of reliable and fast optimization tools for parks of many units. In this thesis, a first attempt of systematic optimization for arrays of the Uppsala University WEC has been proposed. A genetic algorithm (GA) has been used to optimize the geometry of the floater and the damping coefficient of the generator of a single device. Afterwards, the optimal layout of parks up to 14 devices has been studied using two different codes, a continuous and a discrete variables real coded GA. Moreover, the method has been extended to study arrays with devices of different dimensions. A deterministic evaluation of small array layouts in real wave climate has also been carried out. Finally, a physical scale test has been initiated which will allow the validation of the results. A multi--parameter optimization of wave power arrays of the Uppsala University WEC has been shown to be possible and represents a tool that could help to reduce the total cost of electricity, enhance the performance of wave power plants and improve the reliability.