Combinatorial Scheduling & Routing under Uncertainty • Exact MIP Formulation • Heuristics
📍 Lisbon, Portugal • 📱 +351 962 837 935 • 🛂 Residence Permit No. 54S42T272
Optimization Scientist specializing in combinatorial scheduling and routing under uncertainty, surgical block planning, home-care routing, and operational healthcare logistics.
- ⚙️ Mathematical Formulation: I formulate MIP problems from scratch, recognise when the combinatorial structure makes them NP-hard, and choose accordingly: tight LP relaxation, branch-and-cut with problem-specific cuts, or a heuristic that finds near-optimal solutions fast enough to be useful. Fluent in Gurobi, CPLEX and OR-Tools.
- 💡 Applied Impact (6 Years Exp): I designed a reactive parallel-machine scheduling model for a 6-OR hospital with 78% more surgeries per day and unit cost down 55%. I built a VRPTW with time-dependent travel times that hit 100% service level against an 84% deterministic baseline.
- 🔬 Academic Excellence: Co-author of a two-stage stochastic MIP published in EJOR, validated on 18 real disaster scenarios across 13 municipalities. Now PhD at IST Lisbon in stochastic vehicle routing, which mostly means turning new methodological results into solvers that actually run.
| Category | Tools, Methods & Technologies |
|---|---|
| 🧮 MIP / OR | MILP Two-Stage Stochastic Programming Parallel-Machine & Flow-Shop Scheduling VRP / OVRP / VRPTW / TDVRP Network Design Facility Location |
| ⚙️ Solvers | Gurobi CPLEX OR-Tools AMPL GAMS — B&B tuning, problem-specific cut generation, solution pool analysis |
| 🔄 Solution Methods | Branch-and-Cut Column Generation Monte Carlo SAA Large Neighborhood Search (LNS) Metaheuristics |
| 🐍 Python / OR Stack |  Pyomo OR-Tools Pandas NumPy SciPy Matplotlib — model to production pipeline |
| 📈 ML / Forecasting | ARIMA LSTM — demand and overflow forecasting integrated into optimization loops |
| 📊 Data & Reporting |  Power BI Excel Advanced Python dashboards |
(Click to expand details)
🧑🔬 PhD Researcher — Stochastic Vehicle Routing | Instituto Superior Técnico (IST), Lisbon (Apr 2024 – Present)
- Data-Driven Modelling: Modelling container fill-level uncertainty from heterogeneous sensor data; building probabilistic demand scenarios and ML forecasting models that feed directly into routing decisions.
- MIP Formulation: Designing two-stage stochastic MIP models for dynamic waste-collection routing integrating vehicle capacity constraints, depot returns, load redistribution, and overflow recourse actions.
- Algorithm Dev: Developing scalable solution algorithms (branch-and-cut, metaheuristics, rolling-horizon) against exact Gurobi baselines on real Portuguese operator data, managing the solve-time trade-off for daily use.
👨🏫 Assistant Professor & Optimisation Consultant | Pontificia Universidad Javeriana / UAO, Colombia (Aug 2016 – Feb 2022)
- Surgical block scheduling (MILP, AMPL + CPLEX): Designed a reactive two-phase model. Results on a 6-OR hospital: 48 surgeries/day (+78%); elective share 37% → 94%; unit cost per surgery −55%; 12-day backlog resolved in 5 days[cite: 2].
- Home-care routing (OVRP-TW, Python + LNS): Modelled clinician dispatch across Bogota using piecewise-linear travel-time functions from Uber Movement data. Hit 100% service level vs. 84% deterministic baseline; travel time −3h 26m; CO₂ emissions −25%. Validated via Monte Carlo SAA over 30 × 100-client instances.
- Industry Consulting: MIP and simulation models improving logistics KPIs 10–25% across FMCG, automotive, and health sectors.
- Taught advanced OR, scheduling theory, and simulation.
📊 Operations Data Analyst | Western Union Agent (Mar 2014 – Dec 2015)
- Built forecasting models (ARIMA + regression) improving staffing allocation and cutting average customer wait ~20% across 12+ branches.
- Developed standard-time measurement and capacity dashboards enabling faster operational decisions.
- 🏛️ PhD in Engineering & Management | Instituto Superior Técnico, Lisbon (Expected 2028)
- Thesis: Data-Driven Stochastic Optimization for Smart Waste Collection Routing
- 🏭 MSc in Production Engineering | Federal University of São Carlos, Brazil (2018)
- Thesis [PT-Bra]: "Optimization Model for a Humanitarian Supply Network in Brazil"
- 📐 BSc Industrial Engineering + BSc Applied Mathematics | Pontifical Xavierian University, Colombia (2014 / 2015)
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- Thesis Bsc Applied Mathematics [ES]: A hybrid method for calculating the reactivity in nuclear reactor
- 📰 Featured Publication: Alem, D., Bonilla-Londono, H.F., Barbosa-Povoa, A.P., Relvas, S., Ferreira, D., Moreno, A. (2021). "Building disaster preparedness and response capacity in humanitarian supply chains using the Social Vulnerability Index." European Journal of Operational Research, 292(1), 250–275.
- Highlights: Two-stage SMIP (CPLEX) · 18 stochastic disaster scenarios · SoVI-weighted coverage across 13 municipalities · 18 years of real data · cited 30+ times.
- 🏆 Award: Honored as the "Best EJOR Paper Award – EURO 2023".
- 📰 Co-Authored Publication: Suescún-Díaz, D., Bonilla-Londoño, H. F., & Figueroa-Jimenez, J. H. (2016). "Savitzky–Golay filter for reactivity calculation." Journal of Nuclear Science and Technology, 53(7), 944–950.
- Highlights: Mathematical filtering techniques applied to computational calculation processes.
- 🏆 Training: Gurobi Training: Optimization 301 for Data Scientists (Dec 2, 2025)
🗣️ SPOKEN LANGUAGES
- 🇪🇸 Spanish: Native
- 🇵🇹 Portuguese: C1
- 🇬🇧 English: B2
Bringing mathematical optimization to healthcare, smart cities, and complex logistics networks.