To master the complexity in modern vehicle, Original Equipment Manufactures (OEM) attempt to integrate as many functions as possible into the given Electronic Control Unit (ECU), sensors, and actuators without degrading the safety and comfort functionalities. Furthermore scalability, versatility, and performance of products are key to success of electronic development in new modern vehicles. Various functional and nonfunctional requirements obviously shall be fulfilled during development of such complex systems. Choosing of hardware design structure and determination of hardware characteristics are the initial steps during early design phase. The conventional methods for selection of hardware components and topologies are mostly functional-driven. Conventional approaches are largely lacking in versatility and scalability. Due to innovative and complex trend of mechatronic product development, new approaches for hardware decision must be available which support the designers in case of changing (growing) customer demands. One of most important customer requirement for a complex system is reliability. The need for more reliable system design drives up the cost of design and influences the other system characteristics such as weight, power consumption, size, etc. These design goals like reliability, cost potentially impose conflicting requirements on the technical and economic performance of a system design. Hence, visualization and evaluating of the conflicting design preferences and early choosing optimal design are one of the most critical issues during design stage. Many multi-objective optimization approaches have been proposed to tackle this challenge. This dissertation proposes an efficient reliability optimization framework which aids the designers to determine the optimal hardware topology with optimal set of components under known technical and financial restrictions. The proposed reliability optimization framework allows describing the hardware structure of a complex system by a System Reliability Matrix (SRM) and the failure rate vector of involving hardware components. The reliability characteristics of components and the redundancy policy can be varied automatically via the SRM and its corresponding failure rate vector in order to determine optimal solutions. The proposed methodology ultimately addresses the most efficient system architecture (topology) and ascertain the unknown reliability characteristics of hardware components under consideration of financial and technical constraints. It is to be noted that the numerical deterministic search methods and genetic algorithms are applied to optimize the defined objective function under multiple constraints (reliability, cost, weight, size, etc.) and to determine the reliability characteristics of components. A general enumerative algorithm generates all design architectures (topologies) and filters the feasible design architectures (topologies) based on given constraints like budget and etc.