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Stochastic Programming Submissions - 2019

January 2019

Two-stage Stochastic Programming with Linearly Bi-parameterized Quadratic Recourse
Junyi Liu, Ying Cui, Jong-Shi Pang, Suvrajeet Sen

Approximating Two-Stage Chance-Constrained Programs with Classical Probability Bounds
Bismark Singh, Jean-Paul Watson

Admissibility of solution estimators for stochastic optimization
Amitabh Basu, Tu Nguyen, Ao Sun

On Data-Driven Prescriptive Analytics with Side Information: A Regularized Nadaraya-Watson Approach
Chin Pang Ho, Grani Hanasusanto


February 2019

Modeling Flexible Generator Operating Regions via Chance-constrained Stochastic Unit Commitment
Bismark Singh, Bernard Knueven, Jean-Paul Watson

A generalized Benders decomposition-based branch and cut algorithm for two-stage stochastic programs with nonconvex constraints and mixed-binary fi rst and second stage variables
Can Li, Ignacio Grossmann

An Adaptive Sequential Sample Average Approximation Framework for Solving Two-stage Stochastic Programs
Raghu Pasupathy, Yongjia Song

Single cut and multicut SDDP with cut selection for multistage stochastic linear programs: convergence proof and numerical experiments
Vincent Guigues, Michelle Bandarra

Risk-Averse Markov Decision Processes under Parameter Uncertainty with an Application to Slow-Onset Disaster Relief
Merve Merakli, Simge Kucukyavuz

Robust sample average approximation with small sample sizes
E.J. Anderson, A.B. Philpott


March 2019

Multiscale stochastic programming
Martin Glanzer, Georg Ch. Pflug

On a Class of Risk-averse Submodular Maximization Problems
Hao-Hsiang Wu, Simge Kucukyavuz

Partially observable multistage stochastic programming
Oscar Dowson, David P. Morton, Bernardo Pagnoncelli


April 2019

Identifying Effective Scenarios for Sample Average Approximation
Lijian Chen

Distributionally robust optimization with multiple time scales: valuation of a thermal power plant
Wim van Ackooij, Daniela Escobar, Martin Glanzer, Georg Ch. Pflug

Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT
Andreas Anastasiou, Krishnakumar Balasubramanian, Murat A. Erdogdu

A Framework for Solving Chance-Constrained Linear Matrix Inequality Programs
Roya Karimi, Jianqiang Cheng, Miguel Lejeune


May 2019

Stochastic Lipschitz Dynamic Programming
Shabbir Ahmed, Filipe G. Cabral, Bernardo Freitas Paulo da Costa

Risk-Sensitive Variational Bayes: Formulations and Bounds
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao

Solving Chance-Constrained Problems via a Smooth Sample-Based Nonlinear Approximation
Alejandra Pena-Ordieres, James Luedtke, Andreas Waechter

Lagrangian relaxation based heuristics for a chance-constrained optimization model of a hybrid solar-battery storage system
Bismark Singh, Bernard Knueven

Acceleration of SVRG and Katyusha X by Inexact Preconditioning
Yanli Liu, Fei Feng, Wotao Yin


June 2019

Risk Guarantees for End-to-End Prediction and Optimization Processes
Nam Ho-Nguyen, Fatma Kilinc-Karzan

Adaptive Two-stage Stochastic Programming with an Application to Capacity Expansion Planning
Beste Basciftci, Shabbir Ahmed, Nagi Gebraeel

Using Single-Scenario Relaxations to Solve Stochastic Mixed-Integer Programs
David T. Mildebrath, Victor A. Gonzalez, Andrew J. Schaefer, Mehdi Hemmati


July 2019

A Review on the Performance of Linear and Mixed Integer Two-Stage Stochastic Programming Algorithms and Software
Juan Torres, Can Li, Robert Apap, Ignacio Grossmann

The stochastic multi-gradient algorithm for multi-objective optimization and its application to supervised machine learning
S. Liu, L. N. Vicente

A conservative convergent solution for continuously distributed two-stage stochastic optimization problems
Carlos Gamboa, Davi Valladão, Alexandre Street

Logic-based Benders Decomposition and Binary Decision Diagram Based Approaches for Stochastic Distributed Operating Room Scheduling
Cheng Guo, Merve Bodur, Dionne M. Aleman, David R. Urbach


August 2019

Distributionally Robust Optimization: A Review
Hamed Rahimian, Sanjay Mehrotra

Tighter Reformulations using Classical Dawson and Sankoff Bounds for Approximating Two-Stage Chance-Constrained Programs
Bismark Singh

Gaining traction - On the convergence of an inner approximation scheme for probability maximization
Csaba Fabian

Tractable Reformulations of Distributionally Robust Two-stage Stochastic Programs with $\infty-$ Wasserstein Distance
Weijun Xie


September 2019

The risk-averse ultimate pit problem
Gianpiero Canessa, Eduardo Moreno, Bernardo Pagnoncelli

Penalized stochastic gradient methods for stochastic convex optimization with expectation constraints
Xiantao Xiao

Stationary Multistage Programs
Alexander Shapiro, Lingquan Ding

Risk-Averse Optimal Control
Alois Pichler, Ruben Schlottter

Stochastic generalized gradient methods for training nonconvex nonsmooth neural networks
Vladimir I. Norkin

Stochastic Dynamic Linear Programming: A Sequential Sampling-based Multistage Stochastic Programming Algorithm
Harsha Gangammanavar, Suvrajeet Sen


October 2019

Optimal Crashing of an Activity Network with Disruptions
Haoxiang Yang, David Morton

Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens
Fatma Kılınç-Karzan, Simge Küçükyavuz, Dabeen Lee

Improving sample average approximation using distributional robustness
E.J. Anderson, A.B. Philpott

Admissibility of solution estimators for stochastic optimization
Amitabh Basu, Tu Nguyen, Ao Sun

Stochastic Optimization Models of Insurance Mathematics
Yuri M. Ermoliev, Vladimir I. Norkin, Bogdan V. Norkin

A Data-Driven Approach for a Class of Stochastic Dynamic Optimization Problems
Thuener Silva, Davi Valladão, Tito Homem-de-Mello

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization
Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh , Man-Chung Yue, Daniel Kuhn, Wolfram Wiesemann

Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
Viet Anh Nguyen, Shafieezadeh-Abadeh Soroosh, Man-Chung Yue, Daniel Kuhn, Wolfram Wiesemann

Coupled Learning Enabled Stochastic Programming with Endogenous Uncertainty
Junyi Liu, Guangyu Li, Suvrajeet Sen


November 2019

Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization
Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Daniel Kuhn, Peyman Mohajerin Esfahani

Duality and sensitivity analysis of multistage linear stochastic programs
Vincent Guigues, Alexander Shapiro, Yi Cheng


December 2019

Upper and Lower Bounds for Large Scale Multistage Stochastic Optimization Problems: Decomposition Methods
Pierre Carpentier, Jean-Philippe Chancelier, Michel De Lara, François Pacaud

Upper and Lower Bounds for Large Scale Multistage Stochastic Optimization Problems: Application to Microgrid Management
Pierre Carpentier, Jean-Philippe Chancelier, Michel De Lara, François Pacaud

Distributionally Robust Stochastic Dual Dynamic Programming
Daniel Duque, David P. Morton

Stochastic Dynamic Cutting Plane for multistage stochastic convex programs
Vincent Guigues, Renato Monteiro

On Sample Average Approximation for Two-stage Stochastic Programs without Relatively Complete Recourse
Rui Chen, James Luedtke

Stochastic Dual Dynamic Programming for Multistage Stochastic Mixed-Integer Nonlinear Optimization
Shixuan Zhang, Xu Andy Sun

Quasi-Monte Carlo methods for two-stage stochastic programs: Mixed-integer models
Hernan Leoevey, Werner Roemisch

Lagrangian Dual Decision Rules for Multistage Stochastic Mixed Integer Programming
Maryam Daryalal, Merve Bodur, James R. Luedtke


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