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An Approximate Dynamic Programming Approach to Multidimensional Knapsack Problems

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Cited by:

  1. Justin C. Goodson & Jeffrey W. Ohlmann & Barrett W. Thomas, 2013. "Rollout Policies for Dynamic Solutions to the Multivehicle Routing Problem with Stochastic Demand and Duration Limits," Operations Research, INFORMS, vol. 61(1), pages 138-154, February.
  2. Lee, Younsoo & Lee, Kyungsik, 2022. "New integer optimization models and an approximate dynamic programming algorithm for the lot-sizing and scheduling problem with sequence-dependent setups," European Journal of Operational Research, Elsevier, vol. 302(1), pages 230-243.
  3. 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.
  4. Alena Otto & Xiyu Li & Erwin Pesch, 2017. "Two-Way Bounded Dynamic Programming Approach for Operations Planning in Transshipment Yards," Transportation Science, INFORMS, vol. 51(1), pages 325-342, February.
  5. Markus Frey & Rainer Kolisch & Christian Artigues, 2017. "Column Generation for Outbound Baggage Handling at Airports," Transportation Science, INFORMS, vol. 51(4), pages 1226-1241, November.
  6. Luca Bertazzi, 2012. "Minimum and Worst-Case Performance Ratios of Rollout Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 152(2), pages 378-393, February.
  7. Sabah Bushaj & İ. Esra Büyüktahtakın, 2024. "A K-means Supported Reinforcement Learning Framework to Multi-dimensional Knapsack," Journal of Global Optimization, Springer, vol. 89(3), pages 655-685, July.
  8. Ting-Yu Ho & Shan Liu & Zelda B. Zabinsky, 2019. "A Multi-Fidelity Rollout Algorithm for Dynamic Resource Allocation in Population Disease Management," Health Care Management Science, Springer, vol. 22(4), pages 727-755, December.
  9. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
  10. Xi, Haoning & Liu, Wei & Waller, S. Travis & Hensher, David A. & Kilby, Philip & Rey, David, 2023. "Incentive-compatible mechanisms for online resource allocation in Mobility-as-a-Service systems," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 119-147.
  11. Ridvan Gedik & Shengfan Zhang & Chase Rainwater, 2017. "Strategic level proton therapy patient admission planning: a Markov decision process modeling approach," Health Care Management Science, Springer, vol. 20(2), pages 286-302, June.
  12. Yang, Xinan & Vernitski, Alexei & Carrea, Laura, 2016. "An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters," European Journal of Operational Research, Elsevier, vol. 252(3), pages 985-994.
  13. Charles H. Reilly, 2009. "Synthetic Optimization Problem Generation: Show Us the Correlations!," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 458-467, August.
  14. Yuji Nakagawa & Ross J. W. James & César Rego & Chanaka Edirisinghe, 2014. "Entropy-Based Optimization of Nonlinear Separable Discrete Decision Models," Management Science, INFORMS, vol. 60(3), pages 695-707, March.
  15. Goodson, Justin C. & Thomas, Barrett W. & Ohlmann, Jeffrey W., 2017. "A rollout algorithm framework for heuristic solutions to finite-horizon stochastic dynamic programs," European Journal of Operational Research, Elsevier, vol. 258(1), pages 216-229.
  16. Wei, Xiaoyang & Jia, Shuai & Meng, Qiang & Koh, Jimmy, 2024. "Dynamic tugboat deployment and scheduling with stochastic and time-varying service demands," Transportation Research Part B: Methodological, Elsevier, vol. 188(C).
  17. Duygu Aghazadeh & Kadir Ertogral, 2025. "A fix and optimize method based approximate dynamic programming approach for the strategic fleet sizing and delivery planning problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 33(1), pages 91-119, March.
  18. Deane, Jason & Agarwal, Anurag, 2012. "Scheduling online advertisements to maximize revenue under variable display frequency," Omega, Elsevier, vol. 40(5), pages 562-570.
  19. Yilmaz, Dogacan & Büyüktahtakın, İ. Esra, 2024. "An expandable machine learning-optimization framework to sequential decision-making," European Journal of Operational Research, Elsevier, vol. 314(1), pages 280-296.
  20. Marco A. Boschetti & Vittorio Maniezzo & Matteo Roffilli, 2011. "A Fully Distributed Lagrangean Solution for a Peer-to-Peer Overlay Network Design Problem," INFORMS Journal on Computing, INFORMS, vol. 23(1), pages 90-104, February.
  21. Dragos Florin Ciocan & Vivek Farias, 2012. "Model Predictive Control for Dynamic Resource Allocation," Mathematics of Operations Research, INFORMS, vol. 37(3), pages 501-525, August.
  22. Ulmer, Marlin W. & Soeffker, Ninja & Mattfeld, Dirk C., 2018. "Value function approximation for dynamic multi-period vehicle routing," European Journal of Operational Research, Elsevier, vol. 269(3), pages 883-899.
  23. Selvaprabu Nadarajah & Andre A. Cire, 2020. "Network-Based Approximate Linear Programming for Discrete Optimization," Operations Research, INFORMS, vol. 68(6), pages 1767-1786, November.
  24. E A Silver, 2004. "An overview of heuristic solution methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 936-956, September.
  25. Enrique Garza-Escalante & Arturo de la Torre, 2015. "Nacional Monte de Piedad Uses a Novel Social-Value Measure for Allocating Grants Among Charities," Interfaces, INFORMS, vol. 45(6), pages 514-528, December.
  26. 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.
  27. Ulmer, Marlin W. & Thomas, Barrett W., 2020. "Meso-parametric value function approximation for dynamic customer acceptances in delivery routing," European Journal of Operational Research, Elsevier, vol. 285(1), pages 183-195.
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