Over the past few decades, there has been a steep increase in efforts to generate electricity from clean and renewable energy sources so as to reduce consumption of fossil fuels. A considerable amount of research is in progress to explore the scope of various sustainable power sources; among which tidal energy is estimated to have a huge potential. With advancements in technology, it is predicted that electricity from tidal energy would increase in the coming years. It is necessary to have highly efficient generators that can convert tidal energy to electricity. Propeller type generation system using Permanent Magnet Synchronous Machines (PMSMs) are found to be suitable for the application of tidal generators. For the best utilisation of resources, it is essential to improve the performance of these machines in several aspects. And hence, multi-objective optimisation of electrical machines is emerging to be of high significance. The key goal of this thesis is to design, model and optimise a PMSM generator so as to get the desired power while considering other design objectives, including the efficiency, total volume of the machine and weight of magnets. The thesis is divided into two parts. The first part consists of design, modelling and analysis of the PMSM machine. Initially, all the required machine constraints are identified and a topology is selected. An analytical model is built after which the machine is modelled using the Finite Element Method (FEM). The model is analysed where various key characteristics of the machine such as flux linkages, induced EMF, inductance and torque are calculated. This is validated by ensuring that results from FEM model and analytical model match. In order to optimize the machine; certain geometric parameters are varied to locate the dominant geometrical parameters. The second part of the machine consists of optimisation. A multi-objective Genetic Algorithm (GA) optimization is carried out to generate data to search for an optimal design. The three objectives for optimisation are higher efficiency, lower total volume and lesser weight of magnets. The analytical model is used in the optimisation algorithm. Since this is a multi-objective optimisation, a set of solutions (Pareto set) is generated from which a single solution is chosen. This selected solution is applied to the FEM model and thus finally an optimized model of the machine is developed. An analysis is carried out on the optimised model. Finally, the optimised model and the initial model are compared and the results are explained.