Special algorithms have been developed to compute an optimal (s,S) policy for an inventory model with discrete demand and under standard assumptions (stationary data, a well-behaved one-period cost function, full backlogging and the average cost criterion). We present here an iterative algorithm for continuous demand distributions which avoids any form of prior discretization. The method can be viewed as a modified form of policy iteration applied to a Markov decision process with continuous state space. For phase-type distributions, the calculations can be done in closed form.
Federgruen, Awi, and Paul Zipkin. "Computing optimal (s,S) policies in inventory models with continuous demands." Advances in Applied Probability 17, no. 2 (June 1985): 424-442.
Each author name for a Columbia Business School faculty member is linked to a faculty research page, which lists additional publications by that faculty member.
Each topic is linked to an index of publications on that topic.