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This work covers many research aspects of anisotropic synchronous motors, which are synchronous reluctance (SyR), permanent magnet assisted synchronous reluctance (PMaSyR) and interior permanent magnet (IPM) machines. In fact, all these kinds of machines exhibit quite a strong reluctance torque component, hence the name anisotropic. From the early 2000s, the design of electric machines started to deeply rely on finite element analysis (FEA) coupled to automatic optimization algorithms. This workflow enabled the machine designer to make fewer initial sizing hypotheses and to explore a wider design space. The drawbacks of this approach are that the time required is long and that the computational resources needed are quite large. However, the computing performances have always been improving over the years, especially when multi-processor architectures became widespread. Therefore nowadays it is common to employ tens or even hundreds of cores on cluster PCs to perform FEA during optimization runs. The thesis is structured as follows. The first part gives the background knowledge needed to develop the topics covered in the following. This comprehends an introduction to the machines studied, some general knowledge about magnetic materials, some basic concepts about the differential evolution (DE) algorithm, and the drawing of fluid rotor flux-barriers. The second part deals with the analytical modeling of SyR and PMaSyR machines. The complete model is nonlinear and may become convoluted to develop especially in an industrial environment. Therefore, using simplifying assumptions, a handful of simple equations can be derived. This simple model is also extended and applied to asymmetric rotor structures, which try to compensate torque harmonics. The third part focuses on applied multi-objective optimizations coupled to FEA for many different case studies. In particular, a SyR motor (SyRM) for pumping applications is optimized, prototyped and tested. Then, a feasibility study on a very low speed PMaSyR motor is carried out through multi-objective optimization. After that, high speed SyRMs are studied and optimized to understand the power limits of this kind of machine. Finally, the DE multi-objective optimization algorithm is also applied to improve the sensorless-control capabilities of anisotropic machines by design.