The multiobjective genetic algorithm is an effective solution to the complex problem of hardware-software codesign. An extended genetic algorithm (EGA) has been developed that implements a novel selection method with function scaling, adaptive crossover and mutation. This EGA is applied in a codesign optimization stage for dataflow oriented applications and synthesis on field-programmable gate arrays (FPGAs). Its effectiveness is illustrated on the problem of codesign of a self-tuning regulator considering area and performance.