Stochastic depletion problems: Effective myopic policies for a class of dynamic optimization problems
Coauthor(s): Vivek Farias.
This paper presents a general class of dynamic stochastic optimization problems we refer to as Stochastic Depletion
Problems. A number of challenging dynamic optimization problems of practical interest are stochastic depletion
problems. Optimal solutions for such problems are difficult to obtain, both from a pragmatic computational
perspective as also from a theoretical perspective. As such, simple heuristics are desirable. We isolate two simple
properties that, if satisfied by a problem within this class, guarantee that a myopic policy incurs a performance loss
of at most 50% relative to the optimal adaptive control policy for that problem. We are able to verify that these
two properties are satisfied for several interesting families of stochastic depletion problems and as a consequence
identify computationally efficient approximations to optimal control policies for a number of interesting dynamic
stochastic optimization problems.
Source: Mathematics of Operations Research
Chan, Carri, and Vivek Farias. "Stochastic depletion problems: Effective myopic policies for a class of dynamic optimization problems." Mathematics of Operations Research 34, no. 2 (May 2009): 333-350.