Breno A. Beirigo

Researcher in Transport Engineering & Logistics · PhD/MSc in Operations Research · BSc in Computer Science

Education

(Nov 2016 – Mar 2021) Ph.D. in Transport Engineering and Logistics
Delft University of Technology, Delft, The Netherlands

  • Advisers: Prof. Rudy R. Negenborn and Asst. Prof. Frederik Schulte.
  • Thesis: “Dynamic fleet management for autonomous vehicles: Learning- and optimization-based strategies.”

(Mar 2014 – Sep 2016) MSc in Computer Science
Federal University of Viçosa, Viçosa, Brazil

  • Adviser: Asst. Prof. André G. Santos.
  • Thesis: “Single-objective and bi-objective parallel heuristics for the travel planning problem.”
  • Key coursework: Optimization, High-Performance Computing, and Meta-heuristics.

(Mar 2009 – Dec 2014) BSc in Computer Science
Federal University of Viçosa, Viçosa, Brazil

  • Dissertation: “Travel optimizer: A support tool for travel planning.”
  • Silver medal “Presidente Bernardes” in recognition of academic performance (GPA: 8.8/10).

(Feb 2012 – Feb 2013) BSc in Advanced Sensors Applications (exchange program)
Hanze Institute of Technology, Assen, The Netherlands

  • Key coursework: Digital Signal Processing, GIS Practical, and Sensor Networks.

(Feb 2006 – Dec 2008) IT technical degree
Federal Center of Technological Education, Divinópolis, Brazil

  • Key coursework: Web Development, Computer Networks, and Computer Maintenance.

Research Experience

(Nov 2020 – present) Postdoctoral research on Transport Engineering and Logistics
Delft University of Technology, Delft, The Netherlands

  • Advisers: Dr. Bilge Atasoy & Dr. Javier Alonso-Mora
  • Project: “Transportation and Logistics Over Water (TRiLOGy)” of the Netherlands Organization for Scientific Research (NWO)
  • Summary: Designing optimization models that can leverage stochasticity in the demand and network conditions to route and schedule hybrid (over water and land) fleets of (autonomous) vehicles.

(Nov 2016 – Nov 2020) Ph.D. research on Transport Engineering and Logistics
Delft University of Technology, Delft, The Netherlands

  • Advisers: Dr. Frederik Schulte & Dr. Rudy Negenborn / Project: “Integrated Cooperative Automated Vehicle (i-CAVE)” of the Netherlands Organization for Scientific Research (NWO)
  • Summary: Coupled machine learning and optimization through an Approximate Dynamic Programming (ADP) framework to create anticipatory shared autonomous vehicle rebalancing policies that ensure both transport equity and service quality for diversified user profiles.

(Mar 2014 – Sep 2016) MSc research on Optimization
Federal University of Viçosa, Viçosa, Brazil

  • Adviser: Dr. André Gustavo dos Santos / Funding: Capes
  • Summary: Used techniques such as parallel computing, TDSPP framework, NSGA-II framework, and ILS heuristic to determine realistic quality travel schedules for the single-objective and bi-objective versions of the touristic travel planning problem.

(Feb 2012 – Feb 2013) Undergraduate research on Sensitive Innovations
Hanze Institute of Technology, Assen, The Netherlands

  • Adviser: Fenna Feenstra / Funding: BRANETEC
  • Summary: Developed an eye-tracking system and educational software based on the demands of a Dutch Mytylschool (school adapted for disabled children).

(Feb 2011 – Jan 2012) Undergraduate research on Optimization
Federal University of Viçosa, Viçosa, Brazil

  • Adviser: José Elias Cláudio Arroyo / Funding: CNPq
  • Summary: Combined evolutionary algorithms with the LEACH-C framework to form clusters able to increase the power efficiency of wireless sensor networks (WSN).

(Feb 2010 – Jan 2011) Undergraduate research on Optimization
Federal University of Viçosa, Viçosa, Brazil

  • Adviser: Dr. André Gustavo dos Santos / Funding: FUNARBE
  • Summary: Applied heuristics (GRASP and VND) to determine a schedule able to minimize the makespan in a hybrid flexible flow shop environment with sequence-dependent setup times.

Publications

Manuscripts in press

  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. A learning-based optimization approach for autonomous ridesharing platforms with service level contracts and on-demand hiring of idle vehicles. Transportation Science Journal.

Manuscripts in submission

  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. A business class for autonomous mobility-on-demand: Modeling service quality contracts in ridesharing systems. Transportation Research Part C (1st revision round).

Manuscripts in preparation

  • C. Karademir, B. A. Beirigo, Rudy R. Negenborn, and Bilge Atasoy. Real-time dynamic fleet management for waste collection in Amsterdam.
  • L. Larkman, B. A. Beirigo, and F. Schulte. Rebalancing strategies for autonomous mobility-on-demand: A review.

Conference papers

  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. Overcoming mobility poverty with shared autonomous vehicles: A learning-based optimization approach for Rotterdam Zuid. In Proceedings of the 11th International Conference on Computational Logistics, pages 492-506, Enschede, the Netherlands, 2020.
  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. Dual-mode vehicle routing in mixed autonomous and non-autonomous zone networks. In Proceedings of the 21st International Conference on Intelligent Transportation Systems (ITSC), pages 1325-1330, Maui, HI, United States, 2018.
  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. Integrating people and freight transportation using shared autonomous vehicles with compartmentsc. In Proceedings of the 15th IFAC Symposium on Control in Transportation Systems (CTS), pages 392-397, Savona, Italy, 2018.
  • B. A. Beirigo and A. G. dos Santos. Application of NSGA-II framework to the travel planning problem using real-world travel data. In Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC), pages 746-753, Vancouver, Canada, 2016.
  • B. A. Beirigo and A. G. dos Santos. A parallel heuristic for the travel planning problem. In Proceedings of the 15th International Conference on Intelligent Systems Design and Applications (ISDA), pages 283-288, Morocco, 2015.
  • B. A. Beirigo, V. O Matos, J. E. C. Arroyo and L. B. Gonçalves. Genetic algorithm based approach for cluster formation in wireless sensor networks. In XXXVIII Conferencia Latinoamericana En Informatica (CLEI), pages 1-8, Medellin, Colombia, 2012.
  • V. A. Gonçalves, D. M. Reis, E. H. B. Maia, B. A. Beirigo, S. R. Souza, and A. Y. M. Barrientos. Algoritmo genético baseado em chaves aleatórias para o orienteering problem with time windows. In Revista Interdisciplinar de Pesquisa em Engenharia (RIPE), pages 90-104, 2017.

Extended abstracts

  • B. A. Beirigo, F. Schulte, J. Alonso-Mora and R. R. Negenborn. Modeling service class constraints in autonomous mobility-on-demand systems: A data-driven approach for dispatching and rebalancing vehicles. In Proceedings of the 7th INFORMS Transportation Science and Logistics Society Workshop, Vienna, Austria, 2021.
  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. Modeling service class constraints in autonomous mobility-on-demand systems: A data-driven approach for dispatching and rebalancing vehicles. In Proceedings of the 7th INFORMS Transportation Science and Logistics Society Workshop, Vienna, Austria, 2019.
  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. How mobility services can become the better alternative to a self-owned vehicle: Modeling quality in mobility-as-a-service systems. In Proceedings of the International Conference on Integrated Transport (CIT), KTH Royal Institute of Technology, Stockholm, Sweden, 2019.
  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. Reliable mobility-on-demand platforms: Hiring private-owned AVs to ensure service quality. In Proceedings of the TRAIL PhD Congress, Utrecht, the Netherlands, 2019.
  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. Dual-mode vehicle routing in mixed autonomous & non-autonomous zone networks. In Proceedings of the TRAIL PhD Congress, Utrecht, the Netherlands, 2018.
  • B. A. Beirigo, F. Schulte, and R. R. Negenborn. Mixed-purpose shared autonomous vehicles with parcel lockers: Insights on integrating passenger and freight transportation. In Proceedings of the TRAIL PhD Congress, Utrecht, the Netherlands, 2017.

Teaching Experience

(Apr 2021 – Jun 2021) Teaching assistant at Dept. of Maritime & Transport Technology (2h/week)
Delft University of Technology, Delft, The Netherlands

  • Course: Machine Learning for Transport and Multi-Machine Systems
  • Key responsibility: Help students with the practical exercises.

(Apr 2015 – Aug 2016) Lecturer at Department of Informatics (40h/week)
Federal Center of Technological Education, Divinópolis, Brazil

  • Courses taught for BSc Mechatronics Engineering:
    • Android Development
    • Automation via Web
    • Lab. of Programming Languages II
    • Programming Training
  • Courses taught for IT Technical School:
    • Advanced Web Applications
    • Computer Fundamentals

Teacher Assistant at Department of Informatics (2h/week)
Federal University of Viçosa, Viçosa, Brazil

  • Courses taught for mixed BSc degrees:
    • Lab. of Programming Languages

(Feb 2013 – Jul 2013) Teacher at IT Technical School (20h/week)
Municipal School Prefeito Antônio Chequer, Viçosa, Brazil

  • Courses taught:
    • Computer Networks
    • Computer Fundamentals
    • Digital Design

Supervision Experience

Delft University of Technology, Delft, The Netherlands
MSc thesis (co-supervision):

  • Ties Vienks, “Data-driven model predictive control for mobility-on-demand systems” (ongoing).
  • Veerle van der Tas, “Shipper collaboration with restricted zones” (2020).

MSc research assignment:

  • Joris Kortekaas, “Beyond cargo-hitching: Combined people-and-freight systems using modular autonomous vehicles” (ongoing).
  • Marius Pieter van der Tholen, “Optimal capacity of shared vehicles” (2021).
  • Nout Neijmeijer, “On-demand vehicle hiring using reinforcement learning” (2020).

MSc literature assignment:

  • Patrick Wijnands, “Dynamic fleet management in industry 4.0” (2021).
  • Lars Larkman, “Rebalancing strategies for autonomous mobility-on-demand” (2021).
  • Baris Yilmaz, “System-optimal routing in traffic and the deployment of autonomous vehicles” (2018).
  • Marion Tuijp, “Intersection management of the future” (2018).
  • Ryan A. Mulkan, “Integrated logistics and traffic management for autonomous last-mile delivery” (2017).

Conference Activity

Presentation

  • Overcoming mobility poverty with shared autonomous vehicles: A learning-based optimization approach for Rotterdam Zuid. In Proceedings of the 11th International Conference on Computational Logistics, Enschede, the Netherlands, 2020.
  • Reliable mobility-on-demand platforms: Hiring Private-Owned AVs to Ensure Service Quality. Tracks in Transport Conference, TU Delft, Delft, the Netherlands, November 2019.
  • Modeling Service Quality Constraints in Autonomous Mobility-on-Demand Systems: A Data-Driven Approach for Dispatching and Rebalancing Vehicles, INFORMS Transportation Science and Logistics (TSL), Vienna, Austria, June 2019.
  • Dual-Mode Vehicle Routing in Mixed Autonomous & Non-Autonomous Zone Networks, TRAIL PhD Congress, Utrecht, the Netherlands, November 2018.
  • Dual-Mode Vehicle Routing in Mixed Autonomous and Non-Autonomous Zone Networks, 21st IEEE International Conference on Intelligent Transportation Systems, Maui, Hawaii, November 2018.
  • Mixed-Purpose Shared Autonomous Vehicles with Parcel Lockers: Insights on Integrating Passenger and Freight Transportation, TRAIL PhD Congress, Utrecht, the Netherlands, November 2017.
  • Dynamic Fleet Management, i-CAVE program-wide kick-off event, Soesterberg, the Netherlands, June 2016.

Chairing

  • 15th IFAC Symposium on Control in Transportation Systems (CTS), Savona, Italy, June 2018.
  • ICCL2020, University of Twente, Enschede, the Netherlands, September 2020.

Session organization

  • Shared (Autonomous) Mobility, ICCL, University of Twente, Enschede, the Netherlands, September 2020.

Service

Organization

  • Maritime & Technology Department (MTT) internal seminar on “Coordinated Transport & Logistics,” TU Delft, Delft, the Netherlands, ongoing.
  • Maritime & Technology Department (MTT) internal literature exploration seminar on “Transportation, Optimization, and AI,” TU Delft, Delft, the Netherlands, ongoing.

Reviewing

  • Journal of Intelligent Transportation System.
  • Intelligent Transportation Systems Magazine.
  • INFORMS Transportation Science and Logistics (TSL), 2019.
  • 21st IEEE International Conference on Intelligent Transportation Systems, 2018.
  • 15th IFAC Symposium on Control in Transportation Systems (CTS), 2018.
  • TRAIL PhD Congress, 2017-2019.

Guest lecture

  • Approximate Dynamic Programming for Dynamic Fleet Management of Autonomous Vehicles, Federal Center of Technological Education (CEFET-MG), Contagem, Brazil, April 2021.

Committee member

  • Lecturer admission. Position: “Data Structures and Programming Languages,” Department of Informatics at Federal Center of Technological Education (CEFET-MG), Divinópolis, Brazil, March 2016.
  • MSc defense. Prognostics-Driven Supply Chain Optimization in Commercial Aviation, J.P. Sprong, Delft, the Netherlands, September 2019.

Grant proposal

  • Undergraduate research project on the “Team Orienteering Problem with Time Windows” (funding agency: Fapemig), Divinópolis, Brazil, September 2016.

WORK EXPERIENCE

(Mar 2013 – Mar 2014) Intern at Office of International Affairs (20h/week)
Federal University of Viçosa, Viçosa, Brazil

  • Developed web applications (e.g., international agreement search page), offered IT support, and assisted international committees.

Skills

Programming
Python, Gurobi, Java (SE/EE), C++, PHP, HTML, CSS, JavaScript, and MySQL.

Languages
Portuguese (native), English (fluent), and Dutch (basic).