  We consider the problem of optimally designing a system for repeated use
under uncertainty. We develop a modeling framework that integrates design and
operational phases, which are represented by a mixed-integer program and
discounted-cost infinite-horizon Markov decision processes, respectively. We
seek to simultaneously minimize the design costs and the subsequent expected
operational costs. This problem setting arises naturally in several application
areas, as we illustrate through examples. We derive a bilevel mixed-integer
linear programming formulation for the problem and perform a computational
study to demonstrate that realistic instances can be solved numerically.
