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Linear Programming and Sequential Decisions

Citations

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Cited by:

  1. José Niño-Mora, 2006. "Restless Bandit Marginal Productivity Indices, Diminishing Returns, and Optimal Control of Make-to-Order/Make-to-Stock M/G/1 Queues," Mathematics of Operations Research, INFORMS, vol. 31(1), pages 50-84, February.
  2. Sunil Kumar & Kumar Muthuraman, 2004. "A Numerical Method for Solving Singular Stochastic Control Problems," Operations Research, INFORMS, vol. 52(4), pages 563-582, August.
  3. Lodewijk Kallenberg, 2013. "Derman’s book as inspiration: some results on LP for MDPs," Annals of Operations Research, Springer, vol. 208(1), pages 63-94, September.
  4. Alexander Zadorojniy & Segev Wasserkrug & Sergey Zeltyn & Vladimir Lipets, 2019. "Unleashing Analytics to Reduce Costs and Improve Quality in Wastewater Treatment," Interfaces, INFORMS, vol. 49(4), pages 262-268, July.
  5. Vijay V. Desai & Vivek F. Farias & Ciamac C. Moallemi, 2012. "Pathwise Optimization for Optimal Stopping Problems," Management Science, INFORMS, vol. 58(12), pages 2292-2308, December.
  6. Guy Even & Alexander Zadorojniy, 2012. "Strong polynomiality of the Gass-Saaty shadow-vertex pivoting rule for controlled random walks," Annals of Operations Research, Springer, vol. 201(1), pages 159-167, December.
  7. B. Curtis Eaves & Arthur F. Veinott, 2014. "Maximum-Stopping-Value Policies in Finite Markov Population Decision Chains," Mathematics of Operations Research, INFORMS, vol. 39(3), pages 597-606, August.
  8. Yinyu Ye, 2011. "The Simplex and Policy-Iteration Methods Are Strongly Polynomial for the Markov Decision Problem with a Fixed Discount Rate," Mathematics of Operations Research, INFORMS, vol. 36(4), pages 593-603, November.
  9. Ian Post & Yinyu Ye, 2015. "The Simplex Method is Strongly Polynomial for Deterministic Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 40(4), pages 859-868, October.
  10. Archis Ghate & Robert L. Smith, 2013. "A Linear Programming Approach to Nonstationary Infinite-Horizon Markov Decision Processes," Operations Research, INFORMS, vol. 61(2), pages 413-425, April.
  11. Selvaprabu Nadarajah & François Margot & Nicola Secomandi, 2015. "Relaxations of Approximate Linear Programs for the Real Option Management of Commodity Storage," Management Science, INFORMS, vol. 61(12), pages 3054-3076, December.
  12. Liu, Zeyu & Li, Xueping & Khojandi, Anahita, 2022. "The flying sidekick traveling salesman problem with stochastic travel time: A reinforcement learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
  13. Höfferl, F. & Steinschorn, D., 2009. "A dynamic programming extension to the steady state refinery-LP," European Journal of Operational Research, Elsevier, vol. 197(2), pages 465-474, September.
  14. D. P. de Farias & B. Van Roy, 2003. "The Linear Programming Approach to Approximate Dynamic Programming," Operations Research, INFORMS, vol. 51(6), pages 850-865, December.
  15. Guillot, Matthieu & Stauffer, Gautier, 2020. "The Stochastic Shortest Path Problem: A polyhedral combinatorics perspective," European Journal of Operational Research, Elsevier, vol. 285(1), pages 148-158.
  16. Alexander Zadorojniy & Segev Wasserkrug & Sergey Zeltyn & Vladimir Lipets, 2017. "IBM Cognitive Technology Helps Aqualia to Reduce Costs and Save Resources in Wastewater Treatment," Interfaces, INFORMS, vol. 47(5), pages 411-424, October.
  17. Alexander Zadorojniy & Guy Even & Adam Shwartz, 2009. "A Strongly Polynomial Algorithm for Controlled Queues," Mathematics of Operations Research, INFORMS, vol. 34(4), pages 992-1007, November.
  18. K. Helmes & R. H. Stockbridge, 2000. "Numerical Comparison of Controls and Verification of Optimality for Stochastic Control Problems," Journal of Optimization Theory and Applications, Springer, vol. 106(1), pages 107-127, July.
  19. Mehmet U. S. Ayvaci & Oguzhan Alagoz & Elizabeth S. Burnside, 2012. "The Effect of Budgetary Restrictions on Breast Cancer Diagnostic Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 600-617, October.
  20. Diego Klabjan & Daniel Adelman, 2007. "An Infinite-Dimensional Linear Programming Algorithm for Deterministic Semi-Markov Decision Processes on Borel Spaces," Mathematics of Operations Research, INFORMS, vol. 32(3), pages 528-550, August.
  21. Alfredo Torrico & Alejandro Toriello, 2022. "Dynamic Relaxations for Online Bipartite Matching," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 1871-1884, July.
  22. ElHafsi, Mohsen & Fang, Jianxin & Camus, Herve, 2018. "Optimal control of a continuous-time W-configuration assemble-to-order system," European Journal of Operational Research, Elsevier, vol. 267(3), pages 917-932.
  23. Michael O’Sullivan & Arthur F. Veinott, Jr., 2017. "Polynomial-Time Computation of Strong and n -Present-Value Optimal Policies in Markov Decision Chains," Mathematics of Operations Research, INFORMS, vol. 42(3), pages 577-598, August.
  24. Yinyu Ye, 2005. "A New Complexity Result on Solving the Markov Decision Problem," Mathematics of Operations Research, INFORMS, vol. 30(3), pages 733-749, August.
  25. Kurt Helmes & Stefan Röhl, 2008. "A Geometrical Characterization of Multidimensional Hausdorff Polytopes with Applications to Exit Time Problems," Mathematics of Operations Research, INFORMS, vol. 33(2), pages 315-326, May.
  26. Vijay V. Desai & Vivek F. Farias & Ciamac C. Moallemi, 2012. "Approximate Dynamic Programming via a Smoothed Linear Program," Operations Research, INFORMS, vol. 60(3), pages 655-674, June.
  27. Melda Ormeci Matoglu & John Vande Vate, 2011. "Drift Control with Changeover Costs," Operations Research, INFORMS, vol. 59(2), pages 427-439, April.
  28. Dmitry Krass & O. J. Vrieze, 2002. "Achieving Target State-Action Frequencies in Multichain Average-Reward Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 27(3), pages 545-566, August.
  29. Salo, Ahti & Andelmin, Juho & Oliveira, Fabricio, 2022. "Decision programming for mixed-integer multi-stage optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 299(2), pages 550-565.
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