References in zbMATH (referenced in 139 articles )

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  1. Gangammanavar, Harsha; Liu, Yifan; Sen, Suvrajeet: Stochastic decomposition for two-stage stochastic linear programs with random cost coefficients (2021)
  2. Nesbitt, Peter; Blake, Lewis R.; Lamas, Patricio; Goycoolea, Marcos; Pagnoncelli, Bernardo K.; Newman, Alexandra; Brickey, Andrea: Underground mine scheduling under uncertainty (2021)
  3. Pagnoncelli, Bernardo K.; del Canto, Felipe; Cifuentes, Arturo: The effect of regularization in portfolio selection problems (2021)
  4. Zhang, Zhe; Ahmed, Shabbir; Lan, Guanghui: Efficient algorithms for distributionally robust stochastic optimization with discrete scenario support (2021)
  5. Arpón, Sebastián; Homem-de-Mello, Tito; Pagnoncelli, Bernardo K.: An ADMM algorithm for two-stage stochastic programming problems (2020)
  6. Azadi, Zahra; Gangammanavar, Harsha; Eksioglu, Sandra: Developing childhood vaccine administration and inventory replenishment policies that minimize open vial wastage (2020)
  7. Jerinkić, Nataša Krklec; Rožnjik, Andrea: Penalty variable sample size method for solving optimization problems with equality constraints in a form of mathematical expectation (2020)
  8. Liu, Rui Peng: On feasibility of sample average approximation solutions (2020)
  9. Nie, Jiawang; Yang, Liu; Zhong, Suhan: Stochastic polynomial optimization (2020)
  10. Pay, Babak Saleck; Song, Yongjia: Partition-based decomposition algorithms for two-stage stochastic integer programs with continuous recourse (2020)
  11. Wang, Site; Gangammanavar, Harsha; Ekşioğlu, Sandra; Mason, Scott J.: Statistical estimation of operating reserve requirements using rolling horizon stochastic optimization (2020)
  12. Albareda-Sambola, Maria; Martínez-Merino, Luisa I.; Rodríguez-Chía, Antonio M.: The stratified (p)-center problem (2019)
  13. Fei, Xin; Gülpınar, Nalân; Branke, Jürgen: Efficient solution selection for two-stage stochastic programs (2019)
  14. Güney, Evren: An efficient linear programming based method for the influence maximization problem in social networks (2019)
  15. Kumar, Ranjeet; Wenzel, Michael J.; Ellis, Matthew J.; ElBsat, Mohammad N.; Drees, Kirk H.; Zavala, Victor M.: Hierarchical MPC schemes for periodic systems using stochastic programming (2019)
  16. Lamm, Michael; Lu, Shu: Generalized conditioning based approaches to computing confidence intervals for solutions to stochastic variational inequalities (2019)
  17. Vasil’eva, S. N.; Kan, Yu. S.: Approximation of probabilistic constraints in stochastic programming problems with a probability measure kernel (2019)
  18. Arpón, Sebastián; Homem-de-Mello, Tito; Pagnoncelli, Bernardo: Scenario reduction for stochastic programs with conditional value-at-risk (2018)
  19. Byrka, Jaroslaw; Srinivasan, Aravind: Approximation algorithms for stochastic and risk-averse optimization (2018)
  20. Chen, R.; Menickelly, M.; Scheinberg, K.: Stochastic optimization using a trust-region method and random models (2018)

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