Facility layout planning can be addressed from several perspectives, such as operational excellence or the well-being of occupants. These two stances are known to be conflicting since an improvement in one is likely to have a negative impact on the other. Some situations might also require additional requirements to be incorporated into the layout plan that can affect its performance. There are three avenues that drive this research because of these issues, including coping with computational complexity, consideration of infectious diseases for layout planning problems, and increasing the applicability of exact methods for layout practitioners. The first research avenue considers a specific layout problem known as the double-row layout problem. By modifying existing formulations in the literature, the number of binary variables are reduced by at least 25%, thus improving the overall tractability. The primary focus of the second research avenue is to assist restaurant owners in maximizing the expected revenue when operating under pandemic conditions in consideration of the probability distribution of party sizes using stochastic programming. For the final research avenue, a two-phase optimization framework is proposed for generating block layouts and aisle networks for further refining the quality of layout alternatives early in the pre-design phase.