Life evolved over many years, from simple replicating molecules, to complex multicellular organisms. Two key mechanisms for the progression towards complexity are cooperation and specialization. Microbes are ideal for studying how this progression might unfold. On their own, microbes are simple unicellular organisms. However, through cooperative interactions, they can perform many remarkable tasks and can begin to resemble complex life. Understanding how such interactions are formed can also provide insight in how they can be controlled to better suit our needs. In this thesis, we investigate how physical forces influence the evolution of microbial populations and how these processes can be utilized to control evolution.We begin by studying a simple system in which microbes interact through two secreted substances in a fluid environment. Microbes and their secretions are subject to the physical forces of diffusion and advection. We find under certain regimes, microbes form aggregates via the mechanism of a Turing instability. Furthermore, these aggregates grow and fragment to produce new, identical structures. When adding a flow velocity, we find the fluid shear enhances the group fragmentation rate and helps to limit the spread of deleterious cheating mutations.Next we explore the interplay of cooperation and parasitism in motile strategies of swimming microbes. Starting with the physics of flow, drag, and aggregation, we draw ecological and evolutionary implications on the emergence of social and anti-social behavioral strategies in microbial swarms. Through our first-principle simulations, we find that when nutrients are distributed at short distances, microbes evolve to be non-motile. At intermediate nutrient distributions, slow microbes evolve to hitchhike on faster ones, leading to a tragedy of commons where there are no longer fast microbes left to exploit. Finally, when nutrient sources are distributed far apart, fast microbes evolve to adhere to each other, and cooperate to reduce their hydrodynamic drag, benefiting the whole population.Following this we return to our initial model to explore how we can control evolution to better suit our needs. To this end, we study the effects of added chemical perturbations and domain geometry on the social evolution of microbes. Lastly, we introduce an added public good to our model to investigate the evolution of specialization. We find physical factors such as diffusion, flow patterns, and decay rates are as influential as fitness economics in governing the evolution of community structure.