With the proliferation of alternative energy sources, power grids are increasingly dominated by grid-tied power converters. With this development comes the requirement of grid-forming, but current architectures exclude high-voltage applications through serial connectivity. Lattice power grids allow for the generation of both higher voltages and currents than their individual modules by marrying the advantages of serial and parallel connectivity, which include reduced switching and conduction losses, sensorless voltage balancing, and multiport operation. We use graph theory to model lattice power grids and formalize lattice generation processes for square, triangular, and hexagonal lattice grids. This article proposes depth-first-search based algorithms for the control and efficient operation of lattice power grids, achieving voltage and current objectives while minimizing switching losses. Furthermore, we build upon previous algorithms by harnessing multiple input/output operation. The algorithm allows for sequential operation (in which loads are added one by one), simultaneous operation (in which several loads are added at the same time), and combined sequential-simultaneous operation. These methods were applied to a variety of lattice structures, and simulations of dc analysis and pulse train generation were performed. These modeled results validate the proposed algorithms and improve versatility in the operation of lattice power grids in both grid-connected and standalone applications. The potential of applying this method in transcranial magnetic stimulation (TMS) is discussed.