Stochastic Combinatorial Optimization

Stochastic Combinatorial Optimization #

Stochastic Combinatorial Optimization addresses CO problems where some parameters are random or uncertain, requiring robust or adaptive solutions that perform well under uncertainty.

Recent Literature #

1. Robust Combinatorial Optimization with Locally Predictable Uncertainty ICLR, 2023. paper

   Haozhe Sun, Shaoyu Wang, Jiaqi Ma, Chen Gong, Chen Tian

2. Learning Robust Policies for Combinatorial Optimization ICML, 2022. paper, code

   Ankit Anupam, Joon Oh, Jure Leskovec

3. Stochastic Combinatorial Optimization with Oracle Subsampling NeurIPS, 2021. paper

   Paul Grigas, Adam Elmachtoub, Yunchao Liu

4. Adaptive Policies for Stochastic Knapsack Problems Operations Research Letters, 2020. paper

   Wenbo Gao, Oleg V. Pikhurko, Nicholas Harvey

5. Online Stochastic Optimization under Time-Varying Distributions ICML, 2023. paper

   Yudi Zhou, Yinhan He, Jason D. Lee, Yixuan Qiu