When considering the complex problem of developing new multifunctional structures, it is essential to narrow the vast design space and reduce the infinite number of possible solutions to a finite subset of feasible designs. Nature provides examples of ramified, or branched, topologies that form non-intuitive solutions to various structural design problems. This work focuses on the development of a bio-inspired topology optimization framework that couples genetic algorithms with a parallel rewriting system known as a Lindenmayer System (or L-System), which acts as an analogy to the evolutionary process and formalizes the encoding of a 2-D structure. Example design problems and the solutions determined using this novel framework are presented and compared to ideal solutions, where it is shown that a family of branched solutions allowed to evolve over generations can eventually arrive at effective multifunctional structures. Select designs from each example problem are also thickened into 3-D bodies, which are assessed experimentally via fully functional prototypes, demonstrating that the L-System framework is capable of generating realistic solutions for multifunctional structure development.