Maria Minkoff

Papers

Total Citations

372

H-Index

About

Maria Minkoff is a leading figure in approximation algorithms for routing and scheduling problems, with a particular focus on the orienteering problem and its variants. Her seminal work, spanning 2004 to 2007, introduced the first constant-factor approximation algorithm for the rooted orienteering problem—a classic challenge where a traveler must maximize collected prizes within a fixed time budget. This breakthrough, cited over 370 times across her two foundational papers, also defined the Discounted-Reward Traveling Salesman Problem (TSP), a model inspired by robot navigation where rewards decay over time. Minkoff’s algorithms elegantly balance time constraints and prize accumulation, providing provable performance guarantees that have become cornerstones in operations research and theoretical computer science. Her contributions have directly influenced subsequent work on vehicle routing, sensor networks, and mobile robotics, where efficient path planning under resource limits is critical. By tackling these NP-hard problems with rigorous approximation methods, Minkoff has shaped how researchers approach real-world optimization, making her a key reference for students and scholars exploring the intersection of theory and practical decision-making.