6 papers · 1 filter
Learning Optimization Proxies for Sequential Contextual Stochastic Programs: An Order Fulfillment Application
Tinghan Ye, Shuaicheng Tong, Changkun Guan +2
Sequential contextual stochastic programs model real-time decision systems in which each time epoch commits to an action under uncertainty whose consequences propagate into future…
Bilevel Optimization and Heuristic Algorithms for Integrating Latent Demand into the Design of Large-Scale Transit Systems
Hongzhao Guan, Beste Basciftci, Pascal Van Hentenryck
Capturing latent demand has a pivotal role in designing transit services as omitting these riders can lead to poor quality of service and/or additional costs. This paper explores t…
Distributionally Robust Optimization with Multimodal Decision-Dependent Ambiguity Sets
Xian Yu, Beste Basciftci
We consider a two-stage distributionally robust optimization (DRO) model with multimodal uncertainty, where both the mode probabilities and uncertainty distributions could be affec…
Hydrogen Network Expansion Planning considering the Chicken-and-egg Dilemma and Market Uncertainty
Sezen Ece Kayacık, Beste Basciftci, Albert H. Schrotenboer +2
Green hydrogen is thought to be a game changer for reaching sustainability targets. However, the transition to a green hydrogen economy faces a critical challenge known as the `chi…
Dual Sourcing of Green Hydrogen: Balancing Local Production with Stochastic Capacity and Import with Random Yield
Sezen Ece Kayacik, Albert H. Schrotenboer, Iris F. A. Vis +2
Green hydrogen is a critical component for achieving the European Union's 2050 net-zero emissions goal. However, ensuring a reliable and stable supply is challenging, particularly…
Adaptive Two-stage Stochastic Programming with an Analysis on Capacity Expansion Planning Problem
Beste Basciftci, Shabbir Ahmed, Nagi Gebraeel
Multi-stage stochastic programming is a well-established framework for sequential decision making under uncertainty by seeking policies that are fully adapted to the uncertainty. O…