Fully polynomial time approximation schemes for stochastic dynamic programs

Nir Halman, Diego Klabjan, Chung-Lun Li, James B. Orlin, David Simchi-Levi

Abstract: We develop a framework for obtaining (deterministic) Fully Polynomial Time Approximation Schemes (FPTASs) for stochastic univariate dynamic programs with either convex or monotone single-period cost functions. Using our framework, we give the first FPTASs for several NP-hard problems in various fields of research such as knapsack-related problems, logistics, operations management, economics, and mathematical finance.