85 citations · 151 across the 15 of their papers we have counts for
15 papers
Multi-Stage Stochastic Optimization and Reinforcement Learning Approaches for Dynamic Inspection of Infrastructure Systems
Juan-Alberto Estrada-Garcia, Siqian Shen
We study a dynamic inspection problem for infrastructure systems in which multiple vehicles are routed and scheduled to monitor components subject to heterogeneous and stochastic f…
Switching Time Optimization for Binary Quantum Optimal Control
Xinyu Fei, Lucas T. Brady, Jeffrey Larson +2
Quantum optimal control is a technique for controlling the evolution of a quantum system and has been applied to a wide range of problems in quantum physics. We study a binary quan…
A Multi-objective Mixed-integer Programming Approach for Supply Chain Disruption Response with Lead-Time Awareness
Juan-Alberto Estrada-Garcia, Mingjie Bi, Dawn M. Tilbury +2
Supply chain (SC) risk management is influenced by both spatial and temporal attributes of different entities (suppliers, retailers, and customers). Each entity has given capacity…
Risk-Averse Reinforcement Learning via Dynamic Time-Consistent Risk Measures
Xian Yu, Siqian Shen
Traditional reinforcement learning (RL) aims to maximize the expected total reward, while the risk of uncertain outcomes needs to be controlled to ensure reliable performance in a…
A Model-based Multi-agent Framework to Enable an Agile Response to Supply Chain Disruptions
Mingjie Bi, Gongyu Chen, Dawn M. Tilbury +2
Due to the COVID-19 pandemic, the global supply chain is disrupted at an unprecedented scale under uncertain and unknown trends of labor shortage, high material prices, and changin…
Binary Control Pulse Optimization for Quantum Systems
Xinyu Fei, Lucas T. Brady, Jeffrey Larson +2
Quantum control aims to manipulate quantum systems toward specific quantum states or desired operations. Designing highly accurate and effective control steps is vitally important…
On the Value of Multistage Risk-Averse Stochastic Facility Location With or Without Prioritization
Xian Yu, Siqian Shen
We consider a multiperiod stochastic capacitated facility location problem under uncertain demand and budget in each period. Using a scenario tree representation of the uncertainti…
Resource Distribution Under Spatiotemporal Uncertainty of Disease Spread: Stochastic versus Robust Approaches
Beste Basciftci, Xian Yu, Siqian Shen
We consider the problem of optimizing locations of distribution centers (DCs) and plans for distributing resources such as test kits and vaccines, under spatiotemporal uncertaintie…
Sequential Competitive Facility Location: Exact and Approximate Algorithms
Mingyao Qi, Ruiwei Jiang, Siqian Shen
We study a competitive facility location problem (CFLP), where two firms sequentially open new facilities within their budgets, in order to maximize their market shares of demand t…
An Optimization-and-Simulation Framework for Redesigning University Campus Bus System with Social Distancing
Gongyu Chen, Xinyu Fei, Huiwen Jia +2
The outbreak of coronavirus disease 2019 (COVID-19) has led to significant challenges for schools, workplaces and communities to return to operations during the pandemic, requiring…
Multistage Distributionally Robust Mixed-Integer Programming with Decision-Dependent Moment-Based Ambiguity Sets
Xian Yu, Siqian Shen
We study multistage distributionally robust mixed-integer programs under endogenous uncertainty, where the probability distribution of stage-wise uncertainty depends on the decisio…
Distributionally Robust Facility Location Problem under Decision-dependent Stochastic Demand
Beste Basciftci, Shabbir Ahmed, Siqian Shen
Facility location decisions significantly impact customer behavior and consequently the resulting demand in a wide range of businesses. Furthermore, sequentially realized uncertain…
Benders Cut Classification via Support Vector Machines for Solving Two-stage Stochastic Programs
Huiwen Jia, Siqian Shen
We consider Benders decomposition for solving two-stage stochastic programs with complete recourse based on finite samples of the uncertain parameters. We define the Benders cuts b…
Distributionally Robust Partially Observable Markov Decision Process with Moment-based Ambiguity
Hideaki Nakao, Ruiwei Jiang, Siqian Shen
We consider a distributionally robust Partially Observable Markov Decision Process (DR-POMDP), where the distribution of the transition-observation probabilities is unknown at the…
Ambiguous Chance-Constrained Binary Programs under Mean-Covariance Information
Yiling Zhang, Ruiwei Jiang, Siqian Shen
We consider chance-constrained binary programs, where each row of the inequalities that involve uncertainty needs to be satisfied probabilistically. Only the information of the mea…