  The sensitivity of blind gamma-ray pulsar searches in multiple years worth of
photon data, as from the Fermi LAT, is primarily limited by the finite
computational resources available. Addressing this "needle in a haystack"
problem, we here present methods for optimizing blind searches to achieve the
highest sensitivity at fixed computing cost. For both coherent and semicoherent
methods, we consider their statistical properties and study their search
sensitivity under computational constraints. The results validate a multistage
strategy, where the first stage scans the entire parameter space using an
efficient semicoherent method and promising candidates are then refined through
a fully coherent analysis. We also find that for the first stage of a blind
search incoherent harmonic summing of powers is not worthwhile at fixed
computing cost for typical gamma-ray pulsars. Further enhancing sensitivity, we
present efficiency-improved interpolation techniques for the semicoherent
search stage. Via realistic simulations we demonstrate that overall these
optimizations can significantly lower the minimum detectable pulsed fraction by
almost 50% at the same computational expense.
