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The Linear Programming Approach to Approximate Dynamic Programming

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Cited by:

  1. Wang, Tingsong & Meng, Qiang & Tian, Xuecheng, 2024. "Dynamic container slot allocation for a liner shipping service," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).
  2. J. G. Dai & Pengyi Shi, 2019. "Inpatient Overflow: An Approximate Dynamic Programming Approach," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 894-911, October.
  3. Mathias A. Klapp & Alan L. Erera & Alejandro Toriello, 2018. "The One-Dimensional Dynamic Dispatch Waves Problem," Transportation Science, INFORMS, vol. 52(2), pages 402-415, March.
  4. Nikolaos E. Pratikakis & Matthew J. Realff & Jay H. Lee, 2010. "Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(3), pages 211-224, April.
  5. Andrew Ahn & Martin Haugh, 2015. "Linear Programming and the Control of Diffusion Processes," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 646-657, November.
  6. Huseyin Topaloglu & Sumit Kunnumkal, 2006. "Approximate dynamic programming methods for an inventory allocation problem under uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(8), pages 822-841, December.
  7. Daniel Adelman, 2003. "Price-Directed Replenishment of Subsets: Methodology and Its Application to Inventory Routing," Manufacturing & Service Operations Management, INFORMS, vol. 5(4), pages 348-371, May.
  8. Weintraub, Gabriel Y. & Benkard, C. Lanier & Van Roy, Benjamin, 2007. "Computational Methods for Oblivious Equilibrium," Research Papers 1969, Stanford University, Graduate School of Business.
  9. Vural Aksakalli & O. Furkan Sahin & Ibrahim Ari, 2016. "An AO* Based Exact Algorithm for the Canadian Traveler Problem," INFORMS Journal on Computing, INFORMS, vol. 28(1), pages 96-111, February.
  10. Abhijit Gosavi, 2009. "Reinforcement Learning: A Tutorial Survey and Recent Advances," INFORMS Journal on Computing, INFORMS, vol. 21(2), pages 178-192, May.
  11. Dan Zhang, 2011. "An Improved Dynamic Programming Decomposition Approach for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 13(1), pages 35-52, April.
  12. Amin Khademi & Denis R. Saure & Andrew J. Schaefer & Ronald S. Braithwaite & Mark S. Roberts, 2015. "The Price of Nonabandonment: HIV in Resource-Limited Settings," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 554-570, October.
  13. Novoa, Clara & Storer, Robert, 2009. "An approximate dynamic programming approach for the vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 196(2), pages 509-515, July.
  14. Meissner, Joern & Strauss, Arne, 2012. "Network revenue management with inventory-sensitive bid prices and customer choice," European Journal of Operational Research, Elsevier, vol. 216(2), pages 459-468.
  15. Alessio Trivella & Danial Mohseni-Taheri & Selvaprabu Nadarajah, 2023. "Meeting Corporate Renewable Power Targets," Management Science, INFORMS, vol. 69(1), pages 491-512, January.
  16. Oleksandr Shlakhter & Chi-Guhn Lee & Dmitry Khmelev & Nasser Jaber, 2010. "Acceleration Operators in the Value Iteration Algorithms for Markov Decision Processes," Operations Research, INFORMS, vol. 58(1), pages 193-202, February.
  17. Daniela Pucci de Farias & Benjamin Van Roy, 2004. "On Constraint Sampling in the Linear Programming Approach to Approximate Dynamic Programming," Mathematics of Operations Research, INFORMS, vol. 29(3), pages 462-478, August.
  18. Thomas W.M. Vossen & Fan You & Dan Zhang, 2022. "Finite‐horizon approximate linear programs for capacity allocation over a rolling horizon," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2127-2142, May.
  19. Andre P. Calmon & Florin D. Ciocan & Gonzalo Romero, 2021. "Revenue Management with Repeated Customer Interactions," Management Science, INFORMS, vol. 67(5), pages 2944-2963, May.
  20. Santiago R. Balseiro & David B. Brown, 2019. "Approximations to Stochastic Dynamic Programs via Information Relaxation Duality," Operations Research, INFORMS, vol. 67(2), pages 577-597, March.
  21. Daniel Adelman & Diego Klabjan, 2012. "Computing Near-Optimal Policies in Generalized Joint Replenishment," INFORMS Journal on Computing, INFORMS, vol. 24(1), pages 148-164, February.
  22. Zhang, Mimi, 2020. "A heuristic policy for maintaining multiple multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
  23. Dimitris Bertsimas & Velibor V. Mišić, 2016. "Decomposable Markov Decision Processes: A Fluid Optimization Approach," Operations Research, INFORMS, vol. 64(6), pages 1537-1555, December.
  24. Dan Zhang & Daniel Adelman, 2009. "An Approximate Dynamic Programming Approach to Network Revenue Management with Customer Choice," Transportation Science, INFORMS, vol. 43(3), pages 381-394, August.
  25. 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.
  26. Laumer, Simon & Barz, Christiane, 2023. "Reductions of non-separable approximate linear programs for network revenue management," European Journal of Operational Research, Elsevier, vol. 309(1), pages 252-270.
  27. Stefan Heinz & Jörg Rambau & Andreas Tuchscherer, 2014. "Computational bounds for elevator control policies by large scale linear programming," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 79(1), pages 87-117, February.
  28. Somayeh Moazeni & Thomas F. Coleman & Yuying Li, 2016. "Smoothing and parametric rules for stochastic mean-CVaR optimal execution strategy," Annals of Operations Research, Springer, vol. 237(1), pages 99-120, February.
  29. Benjamin Van Roy, 2006. "Performance Loss Bounds for Approximate Value Iteration with State Aggregation," Mathematics of Operations Research, INFORMS, vol. 31(2), pages 234-244, May.
  30. Huseyin Topaloglu & Warren B. Powell, 2005. "A Distributed Decision-Making Structure for Dynamic Resource Allocation Using Nonlinear Functional Approximations," Operations Research, INFORMS, vol. 53(2), pages 281-297, April.
  31. Roberto Steri, 2015. "Collateral-Based Asset Pricing," 2015 Meeting Papers 293, Society for Economic Dynamics.
  32. Yu, Yugang & Luo, Yifei & Shi, Ye, 2022. "Adoption of blockchain technology in a two-stage supply chain: Spillover effect on workforce," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
  33. Dragos Florin Ciocan & Velibor V. Mišić, 2022. "Interpretable Optimal Stopping," Management Science, INFORMS, vol. 68(3), pages 1616-1638, March.
  34. Schütz, Hans-Jörg & Kolisch, Rainer, 2012. "Approximate dynamic programming for capacity allocation in the service industry," European Journal of Operational Research, Elsevier, vol. 218(1), pages 239-250.
  35. Mochen Yang & Gediminas Adomavicius & Alok Gupta, 2019. "Efficient Computational Strategies for Dynamic Inventory Liquidation," Information Systems Research, INFORMS, vol. 30(2), pages 595-615, June.
  36. Lakshman S. Thakur & Mikhail A. Bragin, 2021. "Data Interpolation by Near-Optimal Splines with Free Knots Using Linear Programming," Mathematics, MDPI, vol. 9(10), pages 1-12, May.
  37. Daniel Adelman & Adam J. Mersereau, 2008. "Relaxations of Weakly Coupled Stochastic Dynamic Programs," Operations Research, INFORMS, vol. 56(3), pages 712-727, June.
  38. David B. Brown & James E. Smith & Peng Sun, 2010. "Information Relaxations and Duality in Stochastic Dynamic Programs," Operations Research, INFORMS, vol. 58(4-part-1), pages 785-801, August.
  39. Oscar Dowson & Lea Kapelevich, 2021. "SDDP.jl : A Julia Package for Stochastic Dual Dynamic Programming," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 27-33, January.
  40. Secomandi, Nicola & Seppi, Duane J., 2014. "Real Options and Merchant Operations of Energy and Other Commodities," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 6(3-4), pages 161-331, July.
  41. Daniel Adelman, 2004. "A Price-Directed Approach to Stochastic Inventory/Routing," Operations Research, INFORMS, vol. 52(4), pages 499-514, August.
  42. 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.
  43. Garud N. Iyengar, 2005. "Robust Dynamic Programming," Mathematics of Operations Research, INFORMS, vol. 30(2), pages 257-280, May.
  44. Jalaj Bhandari & Daniel Russo & Raghav Singal, 2021. "A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation," Operations Research, INFORMS, vol. 69(3), pages 950-973, May.
  45. Jaime González & Juan-Carlos Ferrer & Alejandro Cataldo & Luis Rojas, 2019. "A proactive transfer policy for critical patient flow management," Health Care Management Science, Springer, vol. 22(2), pages 287-303, June.
  46. Tatsiana Levina & Yuri Levin & Jeff McGill & Mikhail Nediak, 2011. "Network Cargo Capacity Management," Operations Research, INFORMS, vol. 59(4), pages 1008-1023, August.
  47. Antoine Sauré & Jonathan Patrick & Martin L. Puterman, 2015. "Simulation-Based Approximate Policy Iteration with Generalized Logistic Functions," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 579-595, August.
  48. Oleksandr Shlakhter & Chi-Guhn Lee, 2013. "Accelerated modified policy iteration algorithms for Markov decision processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 78(1), pages 61-76, August.
  49. Daniela Pucci de Farias & Benjamin Van Roy, 2006. "A Cost-Shaping Linear Program for Average-Cost Approximate Dynamic Programming with Performance Guarantees," Mathematics of Operations Research, INFORMS, vol. 31(3), pages 597-620, August.
  50. Qihang Lin & Selvaprabu Nadarajah & Negar Soheili, 2020. "Revisiting Approximate Linear Programming: Constraint-Violation Learning with Applications to Inventory Control and Energy Storage," Management Science, INFORMS, vol. 66(4), pages 1544-1562, April.
  51. Jiaqiao Hu & Michael C. Fu & Vahid R. Ramezani & Steven I. Marcus, 2007. "An Evolutionary Random Policy Search Algorithm for Solving Markov Decision Processes," INFORMS Journal on Computing, INFORMS, vol. 19(2), pages 161-174, May.
  52. Alejandro Toriello & William B. Haskell & Michael Poremba, 2014. "A Dynamic Traveling Salesman Problem with Stochastic Arc Costs," Operations Research, INFORMS, vol. 62(5), pages 1107-1125, October.
  53. Saghafian, Soroush, 2018. "Ambiguous partially observable Markov decision processes: Structural results and applications," Journal of Economic Theory, Elsevier, vol. 178(C), pages 1-35.
  54. Adam Diamant, 2021. "Dynamic multistage scheduling for patient-centered care plans," Health Care Management Science, Springer, vol. 24(4), pages 827-844, December.
  55. Santiago R. Balseiro & Huseyin Gurkan & Peng Sun, 2019. "Multiagent Mechanism Design Without Money," Operations Research, INFORMS, vol. 67(5), pages 1417-1436, September.
  56. Lebedev, Denis & Goulart, Paul & Margellos, Kostas, 2021. "A dynamic programming framework for optimal delivery time slot pricing," European Journal of Operational Research, Elsevier, vol. 292(2), pages 456-468.
  57. Jonathan Patrick & Martin L. Puterman & Maurice Queyranne, 2008. "Dynamic Multipriority Patient Scheduling for a Diagnostic Resource," Operations Research, INFORMS, vol. 56(6), pages 1507-1525, December.
  58. Luiz E. Brandão & James S. Dyer & Warren J. Hahn, 2005. "Response to Comments on Brandão et al. (2005)," Decision Analysis, INFORMS, vol. 2(2), pages 103-109, June.
  59. Daniel Adelman, 2007. "Price-Directed Control of a Closed Logistics Queueing Network," Operations Research, INFORMS, vol. 55(6), pages 1022-1038, December.
  60. Eike Nohdurft & Elisa Long & Stefan Spinler, 2017. "Was Angelina Jolie Right? Optimizing Cancer Prevention Strategies Among BRCA Mutation Carriers," Decision Analysis, INFORMS, vol. 14(3), pages 139-169, September.
  61. Woerner, Stefan & Laumanns, Marco & Zenklusen, Rico & Fertis, Apostolos, 2015. "Approximate dynamic programming for stochastic linear control problems on compact state spaces," European Journal of Operational Research, Elsevier, vol. 241(1), pages 85-98.
  62. Selvaprabu Nadarajah & Andre A. Cire, 2020. "Network-Based Approximate Linear Programming for Discrete Optimization," Operations Research, INFORMS, vol. 68(6), pages 1767-1786, November.
  63. Cai, Yongyang & Judd, Kenneth L. & Lontzek, Thomas S. & Michelangeli, Valentina & Su, Che-Lin, 2017. "A Nonlinear Programming Method For Dynamic Programming," Macroeconomic Dynamics, Cambridge University Press, vol. 21(2), pages 336-361, March.
  64. Vishal Ahuja & John R. Birge, 2020. "An Approximation Approach for Response-Adaptive Clinical Trial Design," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 877-894, October.
  65. 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.
  66. Gabriel Y. Weintraub & C. Lanier Benkard & Benjamin Van Roy, 2010. "Computational Methods for Oblivious Equilibrium," Operations Research, INFORMS, vol. 58(4-part-2), pages 1247-1265, August.
  67. Saied Samiedaluie & Beste Kucukyazici & Vedat Verter & Dan Zhang, 2017. "Managing Patient Admissions in a Neurology Ward," Operations Research, INFORMS, vol. 65(3), pages 635-656, June.
  68. David B. Brown & Martin B. Haugh, 2017. "Information Relaxation Bounds for Infinite Horizon Markov Decision Processes," Operations Research, INFORMS, vol. 65(5), pages 1355-1379, October.
  69. Daniel Adelman, 2007. "Dynamic Bid Prices in Revenue Management," Operations Research, INFORMS, vol. 55(4), pages 647-661, August.
  70. Ken Moon & Patrick Bergemann & Daniel Brown & Andrew Chen & James Chu & Ellen A. Eisen & Gregory M. Fischer & Prashant Loyalka & Sungmin Rho & Joshua Cohen, 2023. "Manufacturing Productivity with Worker Turnover," Management Science, INFORMS, vol. 69(4), pages 1995-2015, April.
  71. Sumit Kunnumkal & Huseyin Topaloglu, 2008. "Exploiting the Structural Properties of the Underlying Markov Decision Problem in the Q-Learning Algorithm," INFORMS Journal on Computing, INFORMS, vol. 20(2), pages 288-301, May.
  72. ManMohan S. Sodhi, 2005. "LP Modeling for Asset-Liability Management: A Survey of Choices and Simplifications," Operations Research, INFORMS, vol. 53(2), pages 181-196, April.
  73. Thomas W. M. Vossen & Dan Zhang, 2015. "Reductions of Approximate Linear Programs for Network Revenue Management," Operations Research, INFORMS, vol. 63(6), pages 1352-1371, December.
  74. Sauré, Antoine & Patrick, Jonathan & Tyldesley, Scott & Puterman, Martin L., 2012. "Dynamic multi-appointment patient scheduling for radiation therapy," European Journal of Operational Research, Elsevier, vol. 223(2), pages 573-584.
  75. John N. Tsitsiklis, 2010. "Commentary ---Perspectives on Stochastic Optimization Over Time," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 18-19, February.
  76. 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.
  77. Michael H. Veatch, 2013. "Approximate Linear Programming for Average Cost MDPs," Mathematics of Operations Research, INFORMS, vol. 38(3), pages 535-544, August.
  78. Somayeh Moazeni & Thomas Coleman & Yuying Li, 2016. "Smoothing and parametric rules for stochastic mean-CVaR optimal execution strategy," Annals of Operations Research, Springer, vol. 237(1), pages 99-120, February.
  79. Pourmoayed, Reza & Nielsen, Lars Relund, 2019. "An approximate dynamic programming approach for sequential pig marketing decisions at herd level," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1056-1070.
  80. 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.
  81. Stephanie Carew & Mahesh Nagarajan & Steven Shechter & Jugpal Arneja & Erik Skarsgard, 2021. "Dynamic Capacity Allocation for Elective Surgeries: Reducing Urgency-Weighted Wait Times," Manufacturing & Service Operations Management, INFORMS, vol. 23(2), pages 407-424, March.
  82. 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).
  83. Daniel Adelman & Adam J. Mersereau, 2013. "Dynamic Capacity Allocation to Customers Who Remember Past Service," Management Science, INFORMS, vol. 59(3), pages 592-612, January.
  84. Tetsuo Iida & Paul H. Zipkin, 2006. "Approximate Solutions of a Dynamic Forecast-Inventory Model," Manufacturing & Service Operations Management, INFORMS, vol. 8(4), pages 407-425, October.
  85. 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.
  86. Matthew S. Maxwell & Mateo Restrepo & Shane G. Henderson & Huseyin Topaloglu, 2010. "Approximate Dynamic Programming for Ambulance Redeployment," INFORMS Journal on Computing, INFORMS, vol. 22(2), pages 266-281, May.
  87. Mengdi Wang, 2020. "Randomized Linear Programming Solves the Markov Decision Problem in Nearly Linear (Sometimes Sublinear) Time," Mathematics of Operations Research, INFORMS, vol. 45(2), pages 517-546, May.
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