Leon Lan - Co-Founder at Applied Routing

Leon Lan

Co-Founder at Applied Routing

Amsterdam, North Holland, Netherlands

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Summary

👤

Senior

🎓

Top School

Leon Lan is a co-founder and routing specialist with eight years of experience building software for routing and scheduling, currently based in Amsterdam. He holds cum laude degrees in Econometrics & Operations Research and Mathematics and completed a PhD candidacy focused on optimization, blending strong theoretical foundations with practical system design. Leon is a hands-on back-end developer and active open-source contributor—his work on ALNS implemented robust stopping criteria, runtime statistics, and architectural refactors that reveal deep familiarity with metaheuristics for vehicle routing. At RoutingLab he translates academic algorithms into production-ready tooling, and his background as a consultant and teacher gives him a knack for turning complex optimization problems into clear, usable software. Notably, his contributions emphasize both algorithmic correctness and observability, tracking runtime and progress for repeatable experiments.

9 years of coding experience

MSc Econometrics and Operations Research, MSc Econometrics and Operations Research at Vrije Universiteit Amsterdam (VU Amsterdam)

BSc Liberal Arts and Sciences, Mathematics, BSc Liberal Arts and Sciences, Mathematics at Amsterdam University College

(Pre-)MSc Mathematics, (Pre-)MSc Mathematics at Delft University of Technology

Semester abroad, Mathematics, Semester abroad, Mathematics at National University of Singapore

Dutch, English, Chinese

Github Skills (2)

python10

testing10

Programming languages (9)

C++ShellTeXMakefileJavaScriptHTMLJupyter NotebookPython

Github contributions (5)

N-Wouda/ALNS

May 2022 - Nov 2022

Adaptive large neighbourhood search (and more!) in Python.

Role in this project:

Back-end Developer

Contributions:96 reviews, 16 commits, 26 PRs in 6 months

Contributions summary:Leon primarily focused on implementing stopping criteria for the Adaptive Large Neighborhood Search (ALNS) algorithm. Their contributions included creating base classes, implementing and testing stopping criteria such as maximum iterations and runtime, and refactoring existing code for improved efficiency. Additionally, they added features to the statistics collection to track algorithm progress, including start time and total runtime, and addressed operator coupling dependencies. The user's work involved significant modifications to the core `ALNS.py` and test files, indicating a deep understanding of the algorithm's inner workings.

pythonadaptive-large-neighbourhood-searchalnsmetaheuristicoperations-research

leonlan/tree-partitioning

Feb 2022 - Feb 2025

Tree partitioning algorithms for power networks

Contributions:2 reviews, 2 PRs, 80 pushes in 2 years 11 months

partitioningcascading-failuresclusteringieeemilp

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