  Genetic Algorithm (GA) has been used in this paper for a new Nyquist based
sub-optimal model reduction and optimal time domain tuning of PID and
fractional order (FO) PI{\lambda}D{\mu} controllers. Comparative studies show
that the new model reduction technique outperforms the conventional H2-norm
based reduced order modeling techniques. Optimum tuning rule has been developed
next with a test-bench of higher order processes via Genetic Programming (GP)
with minimum value of weighted integral error index and control signal. From
the Pareto optimal front which is a trade-off between the complexity of the
formulae and control performance, an efficient set of tuning rules has been
generated for time domain optimal PID and PI{\lambda}D{\mu} controllers.
