Speaker: Assist. Prof. Dr. Tuğrul Cabir Hakyemez

In this seminar, the GiniDispatch approach, which aims to reduce inequalities in driver income and workload, will be discussed. The study presents a framework that includes demand prioritization, driver–request matching, and a Gini-based reward mechanism. The method has been evaluated under different demand conditions and demonstrates that inequalities can be reduced.

Date: April 14, 2026
Time: 13:00–14:00
Location: ISB 210

GiniDispatch: A Gini-Regularized Reinforcement Learning for Joint Earnings and Workload Equity in Taxi Dispatch