Fully polynomial time approximation schemes for stochastic dynamic programs

Authors:
Nir Halman;Diego Klabjan;Chung-Lun Li;James Orlin;David Simchi-Levi
Affiliations:
Massachusetts Institute of Technology, Cambridge, MA;Northwestern University, Evanston, IL;The Hong Kong Polytechnic University;Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA
Venue:
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Year:
2008

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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.