Decomposable Markov Decision Processes: A Fluid Optimization Approach
Published Online:13 Oct 2016https://doi.org/10.1287/opre.2016.1531
References
- (2007) Dynamic bid prices in revenue management. Oper. Res. 55(4):647–661.Link, Google Scholar
- (2008) Relaxations of weakly coupled stochastic dynamic programs. Oper. Res. 56(3):712–727.Link, Google Scholar
- (1987) Linear Programming in Infinite-Dimensional Spaces (John Wiley & Sons, Chichester, UK).Google Scholar
- (1957) Dynamic Programming (Princeton University Press, Princeton, NJ).Google Scholar
- (1961) Adaptive Control Processes: A Guided Tour, Vol. 4 (Princeton University Press, Princeton, NJ).Crossref, Google Scholar
- (1995) Dynamic Programming and Optimal Control, Vol. 1 (Athena Scientific, Belmont, MA).Google Scholar
- (1996) Neuro-Dynamic Programming (Athena Scientific, Belmont, MA).Google Scholar
- (1995) The achievable region method in the optimal control of queueing systems; formulations, bounds and policies. Queueing Systems: Theory Appl. 21(3–4):337–389.Crossref, Google Scholar
- (1996) Conservation laws, extended polymatroids and multiarmed bandit problems; a polyhedral approach to indexable systems. Math. Oper. Res. 21(2):257–306.Link, Google Scholar
- (2000) Restless bandits, linear programming relaxations, and a primal-dual index heuristic. Oper. Res. 48(1):80–90.Link, Google Scholar
- (2011) Theory and applications of robust optimization. SIAM Rev. 53(3):464–501.Crossref, Google Scholar
- (2011) Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations Trends Machine Learn. 3(1):1–122.Crossref, Google Scholar
- (1980) A characterization of waiting time performance realizable by single-server queues. Oper. Res. 28(3):810–821.Link, Google Scholar
- (2003) The linear programming approach to approximate dynamic programming. Oper. Res. 51(6):850–865.Link, Google Scholar
- (2004) On constraint sampling in the linear programming approach to approximate dynamic programming. Math. Oper. Res. 29(3):462–478.Link, Google Scholar
- (1988) Characterization and optimization of achievable performance in general queueing systems. Oper. Res. 36(5):733–741.Link, Google Scholar
- (2013) A linear programming approach to nonstationary infinite-horizon markov decision processes. Oper. Res. 61(2):413–425.Link, Google Scholar
- (2012) Fast multiple-splitting algorithms for convex optimization. SIAM J. Optim. 22(2):533–556.Crossref, Google Scholar
- (2003) A Lagrangian decomposition approach to weakly coupled dynamic optimization problems and its applications. Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
- (1984) Stochastic Models in Operations Research. Vol. 2, Stochastic Optimization (McGraw-Hill, New York).Google Scholar
- (1971) Dynamic Probabilistic Systems, Volume II: Semi-Markov and Decision Processes (Dover, Mineola, NY).Google Scholar
- (2013) A linear programming approach to constrained nonstationary infinite-horizon markov decision processes. Technical Report 13-01, Ann Arbor, MI: University of Michigan, Department of Industrial and Operations Engineering.Google Scholar
- (2007) Approximate Dynamic Programming: Solving the Curses of Dimensionality (Wiley-Interscience, Hoboken, NJ).Crossref, Google Scholar
- (1994) Markov Decision Processes: Discrete Dynamic Stochastic Programming (John Wiley & Sons, Chichester, UK).Crossref, Google Scholar
- (1992) Duality in infinite dimensional linear programming. Math. Programming 53(1–3):79–97.Crossref, Google Scholar
- (2014) Learning to optimize via posterior sampling. Math. Oper. Res. 39(4):1221–1243.Link, Google Scholar
- (1992) Multiclass queueing systems: polymatroidal structure and optimal scheduling control. Oper. Res. 40(3):S293–S299.Link, Google Scholar
- (2002) Neuro-dynamic programming: Overview and recent trends. Handbook of Markov Decision Processes (Springer, New York), 431–459.Crossref, Google Scholar

