Kodirbek Makharov

Learning Equitable and Efficient Shift Rosters with Multi-Objective Deep Reinforcement Learning and Counterfactual Fairness Constraints in Operations

A multi-objective deep reinforcement learning framework for workforce scheduling that integrates Proximal Policy Optimization with a graph neural network encoder, a Conditional Value-at-Risk term for limiting extreme burden concentration, and a counterfactual fairness regularizer for reducing demographic sensitivity in...