  We consider a periodic-review, fixed-lifetime perishable inventory control
problem where demand is a general stochastic process. The optimal solution for
this problem is intractable due to "curse of dimensionality". In this paper, we
first present a computationally efficient algorithm that we call the
marginal-cost dual-balancing policy for perishable inventory control problem.
We then prove that a myopic policy under the so-called marginal-cost accounting
scheme provides a lower bound on the optimal ordering quantity. By combining
the specific lower bound we derive and any upper bound on the optimal ordering
quantity with the marginal-cost dual-balancing policy, we present a more
general class of algorithms that we call the truncated-balancing policy. We
prove that when first-in-first-out (FIFO) is an optimal issuing policy, both of
our proposed algorithms admit a worst-case performance guarantee of two, i.e.
the expected total cost of our policy is at most twice that of an optimal
ordering policy. We further present sufficient conditions that ensure the
optimality of FIFO issuing policy. Finally, we conduct numerical analyses based
on real data and show that both of our algorithms perform much better than the
worst-case performance guarantee, and the truncated-balancing policy has a
significant performance improvement over the balancing policy.
