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DTSTART:20250911T000000
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DTSTART:20251026T030000
RDATE:20261025T030000
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DTSTART:20260329T030000
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SUMMARY:Scheduling at Scale: Building a Railway Timetable Optimizer in Pyt
 hon - Willem Feijen\, Merel Groen
DTSTART;TZID=Europe/Amsterdam:20260911T100500
DTEND;TZID=Europe/Amsterdam:20260911T105000
DTSTAMP:20260809T115151Z
UID:pretalx-pydata-amsterdam2026-XJJUQH@pretalx.com
DESCRIPTION:Modern railway systems operate under tight capacity constraint
 s\, especially during planned maintenance. In this talk\, we present a Pyt
 hon-based timetable optimization system that generates feasible alternativ
 e schedules while staying as close as possible to the original plan.\nWe w
 alk through how a real-world optimization problem\, based on the Periodic 
 Event Scheduling Problem (PESP) and Station Capacity Model (SCM)\, can be 
 translated into a scalable Python application. The talk covers modeling de
 cisions\, solver integration\, and practical trade-offs between solver-agn
 ostic frameworks (Pyomo) and solver-specific implementations (Gurobipy).\n
 Beyond the optimization model itself\, we highlight lessons learned from b
 uilding and maintaining an optimization codebase\, including object-orient
 ed design\, and handling growing model complexity.\nThis talk is aimed at 
 data scientists\, operations researchers\, and software developers interes
 ted in applying optimization techniques in Python to real-world systems.\n
 Attendees will leave with practical insights into modeling\, implementatio
 n choices\, and scaling optimization workflows in Python.
LOCATION:Anomaly
URL:https://pretalx.com/pydata-amsterdam2026/talk/XJJUQH/
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