A Hybrid Genetic Algorithm and Particle Swarm Optimization with Type-2 Fuzzy Sets for Generating Systems of Systems Architectures

Abstract

Both modeling and simulating a system of systems (SoS) are difficult due not only to a changing environment but also the unique behavior that is linked to different participating systems. Generating architectures for a SoS is a multi-objective optimization problem with large number of variables and constraints. The paper presents several of computational intelligence techniques that can generate SoS architectures, such as genetic algorithms (GA), and particle swarm optimization (PSO) combined with Type 2 Fuzzy logic nets. The Maritime search and rescue (SAR) was used as a SoS domain scenario to both implement and demonstrate the architecting methodology. SAR utilizes a variety of systems, including unmanned aerial vehicles (UAV), coordination command control, communication systems and other larger manned vessels. The proposed methodology delivers SoS architects of SAR missions the ability to exploit the interdependence among all systems as well as individual system's inherent characteristics to satisfy stakeholders’ desired attributes. The architect is thus able to design architectures that are robust, efficient, net-centric, and affordable.