Optimization Online


Stochastic Programming Submissions - 2021

January 2021

Heteroscedasticity-aware residuals-based contextual stochastic optimization
Rohit Kannan, Guzin Bayraksan, James Luedtke

Stochastic Dual Dynamic Programming - A Review
Christian Füllner, Steffen Rebennack

Chance-Constrained Optimization: A Review of Mixed-Integer Conic Formulations and Applications
Simge Kucukyavuz, Ruiwei Jiang

March 2021

Exact algorithms for the 0-1 Time-bomb Knapsack Problem
Michele Monaci, Ciara Pike-Burke, Alberto Santini

April 2021

On Convex Lower-Level Black-Box Constraints in Bilevel Optimization with an Application to Gas Market Models with Chance Constraints
Holger Heitsch, René Henrion, Thomas Kleinert, Martin Schmidt

Distributionally Robust Optimal Control and MDP Modeling
Alexander Shapiro

May 2021

Stochastic Variance-Reduced Prox-Linear Algorithms for Nonconvex Composite Optimization
Junyu Zhang, Lin Xiao

On the Convergence of Stochastic Splitting Methods for Nonsmooth Nonconvex Optimization
Jia Hu, Congying Han, Tiande Guo, Tong Zhao

Batch Learning in Stochastic Dual Dynamic Programming
Daniel Ávila, Anthony Papavasiliou, Nils Löhndorf

Central Limit Theorem and Sample Complexity of Stationary Stochastic Programs
Alexander Shapiro, Yi Cheng

On the Value of Multistage Stochastic Facility Location with Risk Aversion
Xian Yu, Siqian Shen, Shabbir Ahmed

June 2021

New Valid Inequalities and Formulation for the Static Chance-constrained Lot-Sizing Problem
Zeyang Zhang, Chuanhou Gao, James Luedtke

July 2021

Dual SDDP for risk-averse multistage stochastic programs
Bernardo Freitas Paulo da Costa, Vincent Leclere

A solution algorithm for chance-constrained problems with integer second-stage recourse decisions
Andrea Lodi, Enrico Malaguti, Michele Monaci, Giacomo Nannicini, Paolo Paronuzzi

August 2021

Confidence Region for Distributed Stochastic Optimization Problem in Stochastic Gradient Tracking Method
Shengchao Zhao, Yongchao Liu

The Sharpe predictor for fairness in machine learning
Suyun Liu, Luis Nunes Vicente

Accelerated Stochastic Peaceman-Rachford Method for Empirical Risk Minimization
Jianchao Bai, Fengmiao Bian, Xiaokai Chang, Lin Du

Scenario Consensus Algorithms for Solving Stochastic and Dynamic Problems
Felipe Lagos

September 2021

Multistage Stochastic Fractionated Intensity Modulated Radiation Therapy Planning
Juyoung Wang, Mucahit Cevik, Merve Bodur, Mark Ruschin

Effective Scenarios in Multistage Distributionally Robust Optimization with a Focus on Total Variation Distance
Hamed Rahimian, Guzin Bayraksan, Tito Homem-de-Mello

Confidence Interval Software for Multi-stage Stochastic Programs
Xiaotie Chen, Sylvain Cazaux, Brian Knight, David Woodruff

October 2021

DFO: A Robust Framework for Data-driven Decision-making with Outliers
Nan Jiang, Weijun Xie

November 2021

Convex Chance-Constrained Programs with Wasserstein Ambiguity
Haoming Shen, Ruiwei Jiang

Stochastic Dual Dynamic Programming for Optimal Power Flow Problems under Uncertainty
Adriana Kiszka, David Wozabal

December 2021

The Value of Coordination in Multi-Market Bidding of Grid Energy Storage
Nils Löhndorf, David Wozabal

Risk-averse Regret Minimization in Multi-stage Stochastic Programs
Mehran Poursoltani, Erick Delage, Angelos Georghiou

Bayesian Distributionally Robust Optimization
Alexander Shapiro, Enlu Zhou, Yifan Lin

Distributionally risk-receptive and risk-averse network interdiction problems with general ambiguity set
Sumin Kang, Manish Bansal

Risk-Averse Stochastic Optimal Control: an efficiently computable statistical upper bound
Vincent Guigues, Alexandre Shapiro, Yi Cheng

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