3 papers
cs.LG2025
Smoothed Online Optimization for Target Tracking: Robust and Learning-Augmented Algorithms
Ali Zeynali, Mahsa Sahebdel, Qingsong Liu +2
We introduce the Smoothed Online Optimization for Target Tracking (SOOTT) problem, a new framework that integrates three key objectives in online decision-making under uncertainty:…
eess.SY2024
Near-Optimal Emission-Aware Online Ride Assignment Algorithm for Peak Demand Hours
Ali Zeynali, Mahsa Sahebdel, Noman Bashir +2
Ridesharing has experienced significant global growth over the past decade and is becoming an integral component of modern transportation systems. However, despite their benefits,…
eess.SY2024
LEAD: Towards Learning-Based Equity-Aware Decarbonization in Ridesharing Platforms
Mahsa Sahebdel, Ali Zeynali, Noman Bashir +2
Ridesharing platforms such as Uber, Lyft, and DiDi have grown in popularity due to their on-demand availability, ease of use, and commute cost reductions, among other benefits. How…