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A unified framework for stochastic optimization

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  1. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
  2. Rempel, M. & Cai, J., 2021. "A review of approximate dynamic programming applications within military operations research," Operations Research Perspectives, Elsevier, vol. 8(C).
  3. Bosse, Alexander & Ulmer, Marlin W. & Manni, Emanuele & Mattfeld, Dirk C., 2023. "Dynamic priority rules for combining on-demand passenger transportation and transportation of goods," European Journal of Operational Research, Elsevier, vol. 309(1), pages 399-408.
  4. Lee, Jinkyu & Bae, Sanghyeon & Kim, Woo Chang & Lee, Yongjae, 2023. "Value function gradient learning for large-scale multistage stochastic programming problems," European Journal of Operational Research, Elsevier, vol. 308(1), pages 321-335.
  5. Benedikt Finnah, 2022. "Optimal bidding functions for renewable energies in sequential electricity markets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 1-27, March.
  6. Marlin W. Ulmer & Barrett W. Thomas & Ann Melissa Campbell & Nicholas Woyak, 2021. "The Restaurant Meal Delivery Problem: Dynamic Pickup and Delivery with Deadlines and Random Ready Times," Transportation Science, INFORMS, vol. 55(1), pages 75-100, 1-2.
  7. Preil, Deniz & Krapp, Michael, 2022. "Bandit-based inventory optimisation: Reinforcement learning in multi-echelon supply chains," International Journal of Production Economics, Elsevier, vol. 252(C).
  8. Ritzinger, Ulrike & Puchinger, Jakob & Rudloff, Christian & Hartl, Richard F., 2022. "Comparison of anticipatory algorithms for a dial-a-ride problem," European Journal of Operational Research, Elsevier, vol. 301(2), pages 591-608.
  9. Ambrosius, M. & Egerer, J. & Grimm, V. & Weijde, A.H. van der, 2020. "Uncertain bidding zone configurations: The role of expectations for transmission and generation capacity expansion," European Journal of Operational Research, Elsevier, vol. 285(1), pages 343-359.
  10. Andres Fielbaum & Maximilian Kronmueller & Javier Alonso-Mora, 2022. "Anticipatory routing methods for an on-demand ridepooling mobility system," Transportation, Springer, vol. 49(6), pages 1921-1962, December.
  11. Ghadimi, Saeed & Powell, Warren B., 2024. "Stochastic search for a parametric cost function approximation: Energy storage with rolling forecasts," European Journal of Operational Research, Elsevier, vol. 312(2), pages 641-652.
  12. Fudong Xie & Ce Wang & Housheng Duan, 2024. "Optimizing Fleet Size in Point-to-Point Shared Demand Responsive Transportation Service: A Network Decomposition Approach," Mathematics, MDPI, vol. 12(19), pages 1-20, September.
  13. Bastian, Nathaniel D. & Lunday, Brian J. & Fisher, Christopher B. & Hall, Andrew O., 2020. "Models and methods for workforce planning under uncertainty: Optimizing U.S. Army cyber branch readiness and manning," Omega, Elsevier, vol. 92(C).
  14. Dvurechensky, Pavel & Gorbunov, Eduard & Gasnikov, Alexander, 2021. "An accelerated directional derivative method for smooth stochastic convex optimization," European Journal of Operational Research, Elsevier, vol. 290(2), pages 601-621.
  15. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  16. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
  17. Visentin, Andrea & Prestwich, Steven & Rossi, Roberto & Tarim, S. Armagan, 2021. "Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming," European Journal of Operational Research, Elsevier, vol. 294(1), pages 91-99.
  18. Lin, Zhiyi & Song, Chunyue & Zhao, Jun & Yin, Huan, 2022. "Improved approximate dynamic programming for real-time economic dispatch of integrated microgrids," Energy, Elsevier, vol. 255(C).
  19. Hughes, Michael S. & Lunday, Brian J., 2022. "The Weapon Target Assignment Problem: Rational Inference of Adversary Target Utility Valuations from Observed Solutions," Omega, Elsevier, vol. 107(C).
  20. Rey, David & Hammad, Ahmed W. & Saberi, Meead, 2023. "Vaccine allocation policy optimization and budget sharing mechanism using reinforcement learning," Omega, Elsevier, vol. 115(C).
  21. Yanbin Chang & Yongjia Song & Burak Eksioglu, 2022. "A stochastic look-ahead approach for hurricane relief logistics operations planning under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 1231-1263, December.
  22. Amorim-Lopes, Mário & Oliveira, Mónica & Raposo, Mariana & Cardoso-Grilo, Teresa & Alvarenga, António & Barbas, Marta & Alves, Marco & Vieira, Ana & Barbosa-Póvoa, Ana, 2021. "Enhancing optimization planning models for health human resources management with foresight," Omega, Elsevier, vol. 103(C).
  23. Chen, Xinwei & Ulmer, Marlin W. & Thomas, Barrett W., 2022. "Deep Q-learning for same-day delivery with vehicles and drones," European Journal of Operational Research, Elsevier, vol. 298(3), pages 939-952.
  24. Avraham, Edison & Raviv, Tal, 2021. "The steady-state mobile personnel booking problem," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 266-288.
  25. Heydar, Mojtaba & Mardaneh, Elham & Loxton, Ryan, 2022. "Approximate dynamic programming for an energy-efficient parallel machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 302(1), pages 363-380.
  26. Mike G. Tsionas & Dionisis Philippas & Constantin Zopounidis, 2023. "Exploring Uncertainty, Sensitivity and Robust Solutions in Mathematical Programming Through Bayesian Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 205-227, June.
  27. Tsaousoglou, Georgios & Ellinas, Petros & Varvarigos, Emmanouel, 2023. "Operating peer-to-peer electricity markets under uncertainty via learning-based, distributed optimal control," Applied Energy, Elsevier, vol. 343(C).
  28. Zhong, Zhiming & Fan, Neng & Wu, Lei, 2024. "Multistage Stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty," European Journal of Operational Research, Elsevier, vol. 318(1), pages 179-199.
  29. Schrotenboer, Albert H. & Veenstra, Arjen A.T. & uit het Broek, Michiel A.J. & Ursavas, Evrim, 2022. "A Green Hydrogen Energy System: Optimal control strategies for integrated hydrogen storage and power generation with wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  30. David Winkelmann & Matthias Ulrich & Michael Romer & Roland Langrock & Hermann Jahnke, 2022. "Dynamic Stochastic Inventory Management in E-Grocery Retailing," Papers 2205.06572, arXiv.org, revised Apr 2024.
  31. Tsay, Calvin, 2024. "A Quantile Neural Network Framework for Twostage Stochastic Optimization," DES - Working Papers. Statistics and Econometrics. WS 43773, Universidad Carlos III de Madrid. Departamento de Estadística.
  32. Faugère, Louis & Klibi, Walid & White, Chelsea & Montreuil, Benoit, 2022. "Dynamic pooled capacity deployment for urban parcel logistics," European Journal of Operational Research, Elsevier, vol. 303(2), pages 650-667.
  33. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
  34. Konrad, Renata A. & Maass, Kayse Lee & Dimas, Geri L. & Trapp, Andrew C., 2023. "Perspectives on how to conduct responsible anti-human trafficking research in operations and analytics," European Journal of Operational Research, Elsevier, vol. 309(1), pages 319-329.
  35. Lunhao Ju & Jiang Jiang & Luofu Wu & Jianbin Sun, 2024. "A Sample Average Approximation Approach for Stochastic Optimization of Flight Test Planning with Sorties Uncertainty," Mathematics, MDPI, vol. 12(19), pages 1-20, September.
  36. Thul, Lawrence & Powell, Warren, 2023. "Stochastic optimization for vaccine and testing kit allocation for the COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 325-338.
  37. Neves-Moreira, Fábio & Amorim, Pedro, 2024. "Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail," International Journal of Production Economics, Elsevier, vol. 267(C).
  38. Romero-Silva, Rodrigo & de Leeuw, Sander, 2021. "Learning from the past to shape the future: A comprehensive text mining analysis of OR/MS reviews," Omega, Elsevier, vol. 100(C).
  39. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid, 2022. "Inventory availability commitment under uncertainty in a dropshipping supply chain," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1155-1174.
  40. Edoardo Fadda & Guido Perboli & Mariangela Rosano & Julien Etienne Mascolo & Davide Masera, 2022. "A Decision Support System for Supporting Strategic Production Allocation in the Automotive Industry," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
  41. Caballero, William N. & Lunday, Brian J. & Uber, Richard P., 2021. "Identifying behaviorally robust strategies for normal form games under varying forms of uncertainty," European Journal of Operational Research, Elsevier, vol. 288(3), pages 971-982.
  42. Soeffker, Ninja & Ulmer, Marlin W. & Mattfeld, Dirk C., 2022. "Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review," European Journal of Operational Research, Elsevier, vol. 298(3), pages 801-820.
  43. Bekker, René & Bharti, Bharti & Lan, Leon & Mandjes, Michel, 2024. "A queueing-based approach for integrated routing and appointment scheduling," European Journal of Operational Research, Elsevier, vol. 318(2), pages 534-548.
  44. Malekipirbazari, Milad & Çavuş, Özlem, 2024. "Index policy for multiarmed bandit problem with dynamic risk measures," European Journal of Operational Research, Elsevier, vol. 312(2), pages 627-640.
  45. Tom Woensel, 2019. "Comments on: Perspectives on integer programming for time-dependent models," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 180-183, July.
  46. Santos, A.M.P. & Fagerholt, Kjetil & Laporte, Gilbert & Guedes Soares, C., 2022. "A stochastic optimization approach for the supply vessel planning problem under uncertain demand," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 209-228.
  47. Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
  48. Daniel Suarez & Camilo Gomez & Andrés L. Medaglia & Raha Akhavan-Tabatabaei & Sthefania Grajales, 2024. "Integrated Decision Support for Disaster Risk Management: Aiding Preparedness and Response Decisions in Wildfire Management," Information Systems Research, INFORMS, vol. 35(2), pages 609-628, June.
  49. Jo~ao F. Doriguello & Alessandro Luongo & Jinge Bao & Patrick Rebentrost & Miklos Santha, 2021. "Quantum algorithm for stochastic optimal stopping problems with applications in finance," Papers 2111.15332, arXiv.org, revised Jul 2023.
  50. Liu, Rui Peng & Shapiro, Alexander, 2020. "Risk neutral reformulation approach to risk averse stochastic programming," European Journal of Operational Research, Elsevier, vol. 286(1), pages 21-31.
  51. Selçuklu, Saltuk Buğra & Coit, David W. & Felder, Frank A., 2020. "Pareto uncertainty index for evaluating and comparing solutions for stochastic multiple objective problems," European Journal of Operational Research, Elsevier, vol. 284(2), pages 644-659.
  52. 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.
  53. Goerigk, Marc & Khosravi, Mohammad, 2023. "Optimal scenario reduction for one- and two-stage robust optimization with discrete uncertainty in the objective," European Journal of Operational Research, Elsevier, vol. 310(2), pages 529-551.
  54. Ekin, Tahir & Naveiro, Roi & Ríos Insua, David & Torres-Barrán, Alberto, 2023. "Augmented probability simulation methods for sequential games," European Journal of Operational Research, Elsevier, vol. 306(1), pages 418-430.
  55. Liu, Kanglin & Liu, Changchun & Xiang, Xi & Tian, Zhili, 2023. "Testing facility location and dynamic capacity planning for pandemics with demand uncertainty," European Journal of Operational Research, Elsevier, vol. 304(1), pages 150-168.
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