Communication needs in avionics and transportation have radically changed over the recent years. Traditionally, the underlying hard real-time networks were designed in a centralized way, focusing on redundancy and isolation. Today, real-time communication is ubiquitous, from large airplanes to small vehicles. The associated networks must support a wide range of applications, and large amounts of data. Centralized approaches from the avionics domain, e.g., AFDX, are too costly, too heavyweight, and not flexible enough for these applications.In this paper we explore a new distributed network architecture designed to support jumbo airliners, but also small aircraft and drones. Communication redundancy is achieved using redundant paths, which have to be adapted and optimized to the application. The main challenge then is to build an optimized network configuration ensuring safety, fault tolerance, timing, and performance of both critical, and non-critical communication. Minimizing volume and weight of the equipment is also mandatory. Since the solution space is too large to be explored in reasonable time, we propose a genetic algorithm. Our experiments show that our algorithm converges quickly and offers solutions of excellent quality. The computed solutions are in the top 2% among the best solutions obtained using an exhaustive exploration. Our approach thus enables system engineers to quickly explore and choose very good solution for their systems.