Linearizing Contextual Bandits with Latent State Dynamics
Elliot Nelson, Debarun Bhattacharjya, et al.
UAI 2022
Analysing track geometry defects is critical for safe and effective railway transportation. Rectifying the appropriate number, types and combinations of geo-defects can effectively reduce the probability of derailments. In this paper, we propose an analytical framework to assist geo-defect rectification decision making. Our major contributions lie in formulating and integrating the following three data-driven models: (1) A track deterioration model to capture the degradation process of different types of geo-defects; (2) A survival model to assess the dynamic derailment risk as a function of track defect and traffic conditions; (3) An optimization model to plan track rectification activities with two different objectives: a cost-based formulation (CF) and a risk-based formulation (RF). We apply these approaches to solve the optimal rectification planning problem for a real-world railway application. We show that the proposed formulations are efficient as well as effective, as compared with existing strategies currently in practice.
Elliot Nelson, Debarun Bhattacharjya, et al.
UAI 2022
Sola Shirai, Debarun Bhattacharjya, et al.
WWW 2023
Debarun Bhattacharjya, Dharmashankar Subramanian, et al.
IJCAI 2020
Dharmashankar Subramanian, Debarun Bhattacharjya, et al.
Big Data 2017