  Optimal random foraging strategy has gained increasing concentrations. It is
shown that L\'evy flight is more efficient compared with the Brownian motion
when the targets are sparse. However, standard L\'evy flight generally cannot
be followed in practice. In this paper, we assume that each flight of the
forager is possibly interrupted by some uncertain factors, such as obstacles on
the flight direction, natural enemies in the vision distance, and restrictions
in the energy storage for each flight, and introduce the tempered L\'evy
distribution $p(l)\sim {\rm e}^{-\rho l}l^{-\mu}$. It is validated by both
theoretical analyses and simulation results that a higher searching efficiency
can be derived when a smaller $\rho$ or $\mu$ is chosen. Moreover, by taking
the flight time as the waiting time, the master equation of the random
searching procedure can be obtained. Interestingly, we build two different
types of master equations: one is the standard diffusion equation and the other
one is the tempered fractional diffusion equation.
